[Numpy-discussion] FFTS for numpy's FFTs (was: Re: Choosing between NumPy and SciPy functions)

Nils Becker nilsc.becker at gmail.com
Thu Oct 30 08:34:04 EDT 2014

> I think that numpy.fft should be left there in its current state
(although perhaps as deprecated). Now scipy.fft should have a good generic
algorithm as default, and easily allow for different implementations to be
accessed through the same interface.

I also agree with the above. But I want to add that in this case it would
be wise to include some (sophisticated) testing suite to ensure that all
possible libraries implement the DFT with high accuracy.
numpy's fftpack (or scipy's) has the advantage that it is old and well
tested. FFTW also provides extensive benchmarks of speed and accuracy.
Other libraries do not. Most users just want an fft function that works and
not bother with details like numerical accuracy. When I encountered such an
issue (https://github.com/hgomersall/pyFFTW/issues/51) it took me really a
long time to track it down to the fft function.

One remark to FFTS: does it implement double precision yet? The
corresponding issue (https://github.com/anthonix/ffts/issues/24) seems to
be still open but I did not look into it. If it does not it is not suited
as a fftpack replacement (I hope I did not overlook some comment about that
in the thread).


PS: although I am a long time user of numpy, I am fairly new to the list.
So hello!
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