[Numpy-discussion] numpy's future (1.1 and beyond): whichdirection(s) ?
Fri Mar 21 05:11:36 CDT 2008
I don't understand why an unification would simplify stuff, it would make
everything so much more difficult :| Instead of dot, you would have a mult()
function to multiply element by element, the same for inv(), so much less
readable when using arrays when arrays are so much more general and generic
So -1 on this.
2008/3/21, Nadav Horesh <email@example.com>:
> I would like to see a unification of matrices and arrays. I often do
> calculation which involve both array processing and linear algebra, and the
> current solution of having function like dot and inv is not aesthetic.
> Switching between array and matrix types (or using .A attribute of a matrix)
> is not convinient either.
> -----הודעה מקורית-----
> מאת: firstname.lastname@example.org בשם David Cournapeau
> נשלח: ו 21-מרץ-08 06:35
> אל: Discussion of Numerical Python
> נושא: [Numpy-discussion] numpy's future (1.1 and beyond):
> whichdirection(s) ?
> numpy 1.0.5 is on the way, and I was wondering about numpy's
> future. I
> myself have some ideas about what could be done; has there been any
> discussion behind what is on 1.1 trac's roadmap ? Some of the things I
> would like to see myself:
> - a framework for plug-in architecture, that is the ability for
> to load/unload some libraries at runtime, plus a common api to access
> the functions. Example: instead of calling directly atlas/etc..., it
> would load the dll at runtime, so that other libraries can be loaded
> instead (numpy itself could load different runtimes depending on the
> CPU, for example: SSE vs SSE2 vs SSE3, multi-thread vs non
> multi-thread). That would require the ability to build loadable
> libraries (numscons, or a new numpy.distutils command).
> - a pure C core library for some common operations. For example, I
> myself would really like to be able to use the fft in some C extensions.
> Numpy has a fft, but I cannot access it from C (well, I could access the
> python fft from C, but that would be... awkward); same for blas/lapack.
> I really like the idea of a numpy "split" into a core C library reusable
> by many C extensions, and python wrappers (in C, cython, ctypes,
> whatever). That would be a huge work, of course, but hopefully can be
> done gradually and smoothly. Only having fft + some basic blas/lapack
> (dot, inv, det, etc...) and some basic functions (beta, gamma, digamma)
> would be great, for example.
> - a highly optimized core library for memory copy, simple
> etc... basically, everything which can see huge improvements when using
> MMX/SSE and co. This is somewhat linked to point 1. This would also
> require more sophisticated memory allocator (aligned, etc...).
> What do people think about this ? Is that a direction numpy developers
> are interested in ?
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