Speed of Python

[Marc 'BlackJack' Rintsch]

On Fri, 07 Sep 2007 22:59:26 +0000, wang frank wrote:

> I also have tried to use numpy to speed it up. However, surprisingly, it is 
> slower than the pure python code.
> 
> Here is the code:
> import  numpy 
> arange=numpy.arange
> nlog=numpy.log
> def bench6(n):
> 	for i in xrange(n):
> 		for j in xrange(1000):
> 			m=j+1
> 			z=nlog(m)
> 			z1=nlog(m+1)
> 			z2=nlog(m+2)
> 			z3=nlog(m+3)
> 			z4=nlog(m+4)
> 			z5=nlog(m+5)
> 			z6=nlog(m+6)
> 			z7=nlog(m+7)
> 			z8=nlog(m+8)
> 			z9=nlog(m+9)
> 	return z9	
> 
> […]
> 
> Anyone know why?

Because you don't really take advantage of `numpy`.  The `numpy.log()`
function can be used with scalars but I guess it is slower because it has
to check if its argument is a scalar or array.  Untested:

from numpy import arange, log as nlog

def bench6(n):
    for dummy in xrange(n):
        for j in xrange(1000):
            z = nlog(arange(j + 1, j + 11))
    return z[-1]