[SciPy-User] improving efficiency of script

John washakie@gmail....
Mon Nov 1 17:38:25 CDT 2010


A) maybe you could share a data file too? (since you shared such a
good code example)

B) is the memory usage growing?

C) not sure if it just for the example, but I'm a little confused
about the 'ncfile'. Is it global? Because you refer to it in the
function, but in the function declaration you call it in_file??

D) These things give me a headache!

E) I would *highly* recommend using weave or F2Py to create a small
little module for the code in the loops. This is really simple, and in
the end a great tool for significant speed ups. Alternatively, I guess
you should see how the code could be vectorized...

-john

PS: These are mostly *off the cuff* thoughts, hope it's a little helpful


On Mon, Nov 1, 2010 at 11:20 PM, Neil Berg <nberg@atmos.ucla.edu> wrote:
> Hi Scipy community,
>
> Attached is a script that interpolates hourly 80-meter wind speeds at each
> grid point.  Interpolation is performed via a cubic spline over the lowest 8
> vertical wind speeds and then output the 80-m wind speed.
>
> Unfortunately, the script is taking about 30 minutes to run for the first
> month, and then takes longer for each successive month.  This is
> demonstrated below:
>
> 195901_3.nc (January)
> ntime= 744  nlat= 54  nlon= 96
> 1734.268457 s for computation.
>
> 195906_3.nc (June)
> ntime= 720  nlat= 54  nlon= 96
> 14578.560365 s for computation.
>
> 195912_3.nc (December)
> ntime= 744  nlat= 54  nlon= 96
> 33484.765078 s for computation.
>
> I don't understand why it takes so much longer for successive months to run;
> they are all roughly the same time dimension and have exactly the same
> latitude and longitude dimensions.  Do you have any ideas why this is
> happening?  Also, do you have any suggestions on how to shorten the length
> of time it takes to run the script in the first place?  The "tim_idx"
> for-loop surrounding the interpolation procedure is the dominant factor
> increasing the run time, but I am stuck on possible ways to shave time off
> these steps.
>
> Thank you in advance,
>
> Neil Berg
> nberg@atmos.ucla.edu
> ___________________
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> Python/scipy 2.6.1
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