[Numpy-discussion] A random.normal function with stdev as array

[Eric Emsellem]

Hi,

I am trying to optimize a code where I derive random numbers many times 
and having an array of values for the stdev parameter.

I wish to have an efficient way of doing something like:
##################
stdev = array([1.1,1.2,1.0,2.2])
result = numpy.zeros(stdev.shape, Float)
for i in range(len(stdev)) :
   result[i] = numpy.random.normal(0, stdev[i])
##################

In my case,  stdev can in fact be an array of a few millions floats... 
so I really need to optimize things.

Any hint on how to code this efficiently ?

And in general, where could I find tips for optimizing a code where I 
unfortunately have too many loops such as "for i in range(Nbody) : " 
with Nbody being > 10^6 ?

thanks!
Eric