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
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