[Numpy-discussion] Proposed Roadmap Overview
Paul Anton Letnes
paul.anton.letnes@gmail....
Mon Feb 20 13:55:26 CST 2012
On 20. feb. 2012, at 16:29, Sturla Molden wrote:
> Den 20.02.2012 08:35, skrev Paul Anton Letnes:
>> In the language wars, I have one question. Why is Fortran not being considered? Fortran already implements many of the features that we want in NumPy:
>
> Yes ... but it does not make Fortran a systems programming language.
> Making NumPy is different from using it.
>
>> - slicing and similar operations, at least some of the fancy indexing kind
>> - element-wise array operations and function calls
>> - array bounds-checking and other debugging aid (with debugging flags)
>
> That is nice for numerical computing, but not really needed to make NumPy.
>
>
>> - arrays that mentally map very well onto numpy arrays. To me, this spells +1 to ease of contribution, over some abstract C/C++ template
>
> Mentally perhaps, but not binary. NumPy needs uniformly strided memory
> on the binary level. Fortran just gives this at the mental level. E.g.
> there is nothing that dictates a Fortran pointer has to be a view, the
> compiler is free to employ copy-in copy-out. In Fortran, a function call
> can invalidate a pointer. One would therefore have to store the array
> in an array of integer*1, and use the intrinsic function transfer() to
> parse the contents into NumPy dtypes.
>
>> - in newer standards it has some nontrivial mathematical functions: gamma, bessel, etc. that numpy lacks right now
>
> That belongs to SciPy.
I don't see exactly why. Why should numpy have exponential but not gamma functions? The division seems kinda arbitrary. Not that I am arguing violently for bessel functions in numpy.
>> - compilers that are good at optimizing for floating-point performance, because that's what Fortran is all about
>
> Insanely good, but not when we start to do the (binary, not mentally)
> strided access that NumPy needs. (Not that C compilers would be any better.)
>
>
>
>> - not Fortran as such, but BLAS and LAPACK are easily accessed by Fortran
>> - possibly other numerical libraries that can be helpful
>> - Fortran has, in its newer standards, thought of C interoperability. We could still keep bits of the code in C (or even C++?) if we'd like to, or perhaps f2py/Cython could do the wrapping.
>
> Not f2py, as it depends on NumPy.
>
> - some programmers know Fortran better than C++. Fortran is at least used by many science guys, like me.
>
>
> That is a valid arguments. Fortran is also much easier to read and debug.
>
>
> Sturla
Thanks for an excellent answer, Sturla - very informative indeed.
Paul.
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