Problem solved. I had one last for loop in there. Its odd that as I gradually got rid of the for loops, the speed went down, but when I got rid of the last on, bingo! That routine now runs at a 1/10 of its original time. Rob. Rob wrote:
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.
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