[SciPy-user] Correlate Times?

Johann Cohen-Tanugi cohen@slac.stanford....
Fri Jan 18 00:56:01 CST 2008


hi,
talking about cleanup, I see that the delaunay package is duplicated in 
scipy.sandbox and scikits. The files seem fairly identical....
best,
Johann

Travis E. Oliphant wrote:
> Ryan May wrote:
>   
>> Hey,
>>
>> Can someone explain this to me?
>>
>> In [3]: import scipy as S
>>
>> In [5]: import scipy.signal as SS
>>
>> In [6]: from numpy.random import rand
>>
>> In [7]: up = rand(18000)
>>
>> In [10]: %timeit N.correlate(up,up,mode='full')
>> 10 loops, best of 3: 829 ms per loop
>>
>> In [11]: %timeit S.correlate(up,up,mode='full')
>> 10 loops, best of 3: 827 ms per loop
>>
>> In [12]: %timeit SS.correlate(up,up,mode='full')
>> 10 loops, best of 3: 11.5 s per loop
>>
>> Is this a configuration problem?  If not, why does
>> scipy.signal.correlate even exist?
>>   
>>     
>
> scipy.signal.correlate is a N-d correlation algorithm as has been 
> noted.  It is going to be slower for 1-d arrays.  Now, there is nothing 
> wrong with checking for that case and calling the 1-d version, it's just 
> never been done (probably because people who only need 1-d correlation 
> are already just using numpy.correlate).
>
> ndimage also has N-d correlation inside it which was created much 
> later.  I think it is currently faster (but with different arguments 
> that I don't fully understand so, I'm not sure what command would be 
> equivalent.
>
> Try scipy.ndimage.correlate  and see how fast it is.
>
> This is part of the kind of clean-up that SciPy really needs.
>
> -Travis
>
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