[Numpy-discussion] Re: my Numpy statements are slower than indexed formulations in some cases
Rob
rob at pythonemproject.com
Fri Dec 21 23:46:23 EST 2001
Rob wrote:
>
> I have a number of thse routines in some EM code. I've tried to
> Numpyize them, but end up with code that runs even slower.
>
> Here is the old indexed routing:
>
> -----------------
> for JJ in range(0,TotExtMetalEdgeNum):
>
> McVector+=Ccc[0:TotExtMetalEdgeNum,JJ] * VcVector[JJ]
> ----------------
>
> Here is the Numpy version:
>
> ---------------------
> McVector= add.reduce(transpose(Ccc[...] * VcVector[...]))
> ---------------------
>
> I wonder if there is another faster way to do this? Thanks, Rob.
>
> --
I did speed things up just a tiny bit by using:
add.reduce(Ccc*VcVector,1) instead of
add.reduce(transpose(Ccc*VcVector).
But I'm still running way slower than an indexed array scheme. Rob.
> The Numeric Python EM Project
>
> www.pythonemproject.com
--
The Numeric Python EM Project
www.pythonemproject.com
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