a.schmolck(a)gmx.net [mailto:a.schmolck@gmx.net] wrote:
>
> Numeric is an impressively powerful and in many respects easy and
> comfortable to use package (e.g. it's sophisticated slicing
> operations, not to mention the power and elegance of the underlying
> python language) and one would hope that it can one day replace Matlab
> (which is both expensive and a nightmare as a programming language) as
> a standard platform for numerical calculations.
I'm in much the same boat, only with Gauss as the language I want
to replace.
> There is however a problem that, for the use to which I want
> to put Numeric, runs deeper and provides me with quite a headache:
>
> Two essential matrix operations (matrix-multiplication and
> transposition (which is what I am mainly using) are both considerably
>
> a) less efficient and
> b) less notationally elegant
>
> under Numeric than under Matlab.
These are my two problems as well. I can live with the clumsy function
call interface to the matrix ops, but the loss of efficiency is a
real killer for me. In my code, Gauss is about 8-10x faster than
Numpy, which is a killer speed loss. (And Gauss is modestly slower
than C, though I don't care about this because the Gauss is fast
enough.)
Right now, I have a data-mining program that I prototyped in
Numpy and am now rewriting in C. Because Numpy isn't fast enough,
I have wasted close to a week on this rewrite. This sounds bitter,
but it's not meant to. I have to deploy on VMS, and after we had
gotten Numpy working on OpenVMS I really hoped that the Alpha would
fast enough that I could just use the Python prototype.
--
Neel Krishnaswami
neelk(a)cswcasa.com