[SciPy-Dev] Scipy 1.0 roadmap
Tue Sep 24 13:05:33 CDT 2013
On Tue, Sep 24, 2013 at 2:29 PM, Christoph Deil <
> On Sep 24, 2013, at 1:28 PM, Nathaniel Smith <email@example.com> wrote:
> > On Mon, Sep 23, 2013 at 8:51 AM, Dag Sverre Seljebotn
> > <firstname.lastname@example.org> wrote:
> >> On 09/21/2013 08:57 PM, Ralf Gommers wrote:
> >>> fftpack
> >>> ```````
> >>> Needed:
> >>> - solve issues with single precision: large errors, disabled for
> >>> difficult sizes
> >>> - fix caching bug
> >>> - Bluestein algorithm nice to have, padding is alternative
> >> A battle-tested Bluestein is included in Martin Reinecke's C port of
> >> FFTPACK.
> >> https://github.com/dagss/libfftpack
> >> As you can see in the readme there were a couple of changes to FFTPACK
> >> to improve accuracy for large primes.
> > If this is nicely-licensed C code that provides a superset of
> > scipy.fftpack's functionality, ought we to merge it into *numpy*.fft
> > and deprecate scipy.fftpack? (I'm a little confused at what exactly
> > the difference between the numpy and scipy modules is in this case,
> > except that of course the scipy version needs a fortran compiler.)
> > -n
> On that note … a thought for scipy 1.0 :
> Does scipy absolutely need Fortran in general?
> Or are there equivalent C or C++ packages that might be used instead?
> Getting rid of Fortran code would simplify life for Mac users (and maybe
> Windows or even Linux).
> I don't really know how much Fortran is used in scipy or libraries it
> depends on, or how much of a problem Fortran really is.
> I'm just asking if getting rid of Fortran is an option even worth
> considering for scipy 1.0.
scipy contains approximately 100k LOC of often non trivial code. Lots of
them most likely don't have an equivalent in any other language (ARPACK,
specfunc, etc...), and few people both have the domain expertise and the
will to port those things. That + the fact that fortran is often more
appropriate than C/C++ anyway for numeric work.
The issue of fortran on mac is partly Apple's fault for screwing up their
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