On Thu, Jul 15, 2010 at 9:41 AM, David Goldsmith <[email protected]>wrote:
> On Thu, Jul 15, 2010 at 3:20 AM, Martin Raspaud <[email protected]>wrote: > >> -----BEGIN PGP SIGNED MESSAGE----- >> 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. >> >> Hi, >> >> 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. >> > > I get the picture: in the docstring, refer people to fftw. > > DG > I can't find this fftw function in either numpy or scipy - where is it? DG
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