[Numpy-discussion] Slicing slower than matrix multiplication?
Jasper van de Gronde
Mon Dec 14 11:20:32 CST 2009
Francesc Alted wrote:
> A Monday 14 December 2009 17:09:13 Francesc Alted escrigué:
>> The things seems to be worst than 1.6x times slower for numpy, as matlab
>> orders arrays by column, while numpy order is by row. So, if we want to
>> compare pears with pears:
>> For Python 600x200:
>> Add a row: 0.113243 (1.132425e-05 per iter)
>> For Matlab 600x200:
>> Add a column: 0.021325 (2.132527e-006 per iter)
> Mmh, I've repeated this benchmark on my machine and got:
> In : timeit E + Xi2[P/2]
> 100000 loops, best of 3: 2.8 µs per loop
> that is, very similar to matlab's 2.1 µs and quite far from the 11 µs you are
> getting for numpy in your machine... I'm using a Core2 @ 3 GHz.
I'm using Python 2.6 and numpy 1.4.0rc1 on a Core2 @ 1.33 GHz
(notebook). I'll have a look later to see if upgrading Python to 2.6.4
makes a difference.
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