[Numpy-discussion] numpy.fft, yet again

Martin Raspaud martin.raspaud@smhi...
Thu Jul 15 05:20:42 CDT 2010

Hash: SHA1

David Goldsmith skrev:
>     Interesting comment: it made me run down the fftpack tutorial
>     <http://docs.scipy.org/scipy/docs/scipy-docs/tutorial/fftpack.rst/>
>     josef has alluded to in the past to see if the suggested pointer
>     could point there without having to write a lot of new content. 
>     What I found was that although the scipy basic fft functions don't
>     support it (presumably because they're basically just wrappers for
>     the numpy fft functions), scipy's discrete cosine transforms support
>     an "norm=ortho" keyword argument/value pair that enables the
>     function to return the unitary versions that you describe above. 
>     There isn't much narrative explanation of the issue yet, but it got
>     me wondering: why don't the fft functions support this?  If there
>     isn't a "good" reason, I'll go ahead and submit an enhancement ticket.
> Having seen no post of a "good reason," I'm going to go ahead and file
> enhancement tickets.


I have worked on fourier transforms and I think normalization is generally seen
as a whole : fft + ifft should be the identity function, thus the necessity of a
normalization, which often done on the ifft.

As one of the previous poster mentioned, sqrt(len(x)) is often seen as a good
compromise to split the normalization equally between fft and ifft.

In the sound community though, the whole normalization often done after the fft,
such that looking at the amplitude spectrum gives the correct amplitude values
for the different components of the sound (sinusoids).

My guess is that normalization requirements are different for every user: that's
why I like the no normalization approach of fftw, such that anyone does whatever
he/she/it wants.

Best regards,
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