[Numpy-discussion] FFTS for numpy's FFTs (was: Re: Choosing between NumPy and SciPy functions)
cournape at gmail.com
Tue Oct 28 05:41:43 EDT 2014
On Tue, Oct 28, 2014 at 9:19 AM, Charles R Harris <charlesr.harris at gmail.com
> On Tue, Oct 28, 2014 at 1:32 AM, Jerome Kieffer <Jerome.Kieffer at esrf.fr>
>> On Tue, 28 Oct 2014 04:28:37 +0000
>> Nathaniel Smith <njs at pobox.com> wrote:
>> > It's definitely attractive. Some potential issues that might need
>> > with, based on a quick skim:
>> In my tests, numpy's FFTPACK isn't that bad considering
>> * (virtually) no extra overhead for installation
>> * (virtually) no plan creation time
>> * not that slower for each transformation
>> Because the plan creation was taking ages with FFTw, numpy's FFTPACK was
>> often faster (overall)
> Ondrej says that f90 fftpack (his mod) runs faster than fftw.
I would be interested to see the benchmarks for this.
The real issue with fftw (besides the license) is the need for plan
computation, which are expensive (but are not needed for each transform).
Handling this in a way that is user friendly while tweakable for advanced
users is not easy, and IMO more appropriate for a separate package.
The main thing missing from fftpack is the handling of transform sizes that
> are not products of 2,3,4,5.
Strickly speaking, it is handled, just not through an FFT (it goes back to
the brute force O(N**2)).
I made some experiments with the Bluestein transform to handle prime
transforms on fftpack, but the precision seemed to be an issue. Maybe I
should revive this work (if I still have it somewhere).
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