[Numpy-discussion] python's random.random() faster than numpy.random.rand() ???

[Stefan van der Walt]

Hi Mark

On Fri, Jan 26, 2007 at 10:17:58AM -0700, Mark P. Miller wrote:
> I've recently been working with numpy's random number generators and 
> noticed that python's core random number generator is faster than 
> numpy's for the uniform distribution.
> 
> In other words,
> 
> for a in range(1000000):
>      b = random.random()    #core python code
> 
> is substantially faster than
> 
> for a in range(1000000):
>      b = numpy.random.rand()    #numpy code

With numpy, you can get around the for-loop by doing

N.random.random(1000000)

which is much faster:

In [7]: timeit for i in range(10000): random.random()
100 loops, best of 3: 3.92 ms per loop

In [8]: timeit N.random.random(10000)
1000 loops, best of 3: 514 µs per loop

Cheers
Stéfan