Hi,
While profiling some code, I noticed that sum in numpy is kind of
slow once you use axis argument:
import numpy as N
a = N.random.randn(1e5, 30)
%timeit N.sum(a) #-> 26.8ms
%timeit N.sum(a, 1) #-> 65.5ms
%timeit N.sum(a, 0) #-> 141ms
Now, if I use some tricks, I get:
%timeit N.sum(a) #-> 26.8 ms
%timeit N.dot(a, N.ones(a.shape[1], a.dtype)) #-> 11.3ms
%timeit N.dot(N.ones((1, a.shape[0]), a.dtype), a) #-> 15.5ms
I realize that dot uses optimized libraries (atlas in my case) and all,
but is there any way to improve this situation ?
Cheers,
David
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