[Numpy-discussion] Distance Matrix speed

[Christopher Barker]

Bruce Southey wrote:
> Please run the exact same code in Matlab that you are running in
> NumPy. Many of Matlab functions are very highly optimized so these are
> provided as binary functions. I think that you are running into this
> so you are not doing the correct comparison

He is doing the correct comparison: if Matlab has some built-in compiled 
utility functions that numpy doesn't -- it really is faster!

It looks like other's suggestions show that well written numpy code is 
plenty fast, however.

One more suggestion I don't think I've seen: numpy provides a built-in 
compiled utility function: hypot()

 >>> x = N.arange(5)
 >>> y = N.arange(5)
 >>> N.hypot(x,y)
array([ 0.        ,  1.41421356,  2.82842712,  4.24264069,  5.65685425])
 >>> N.sqrt(x**2 + y**2)
array([ 0.        ,  1.41421356,  2.82842712,  4.24264069,  5.65685425])

Timings:
 >>> timeit.Timer('N.sqrt(x**2 + y**2)','import numpy as N; x = 
N.arange(5000); y = N.arange(5000)').timeit(100)
0.49785208702087402
 >>> timeit.Timer('N.hypot(x,y)','import numpy as N; x = N.arange(5000); 
y = N.arange(5000)').timeit(100)
0.081479072570800781

A factor of 6 improvement.

-Chris




-- 
Christopher Barker, Ph.D.
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