[Numpy-discussion] python is cool

[Roland Schulz]

Hi,

I think the best way to solve this issue to not use a state at all. It is
fast, reproducible even in parallel (if wanted), and doesn't suffer from
the shared issue. Would be nice if numpy provided such a stateless RNG as
implemented in Random123: www.deshawresearch.com/resources_random123.html

Roland

On Tue, May 12, 2015 at 2:18 PM, Neal Becker <ndbecker2 at gmail.com> wrote:

> In order to make sure all my random number generators have good
> independence, it is a good practice to use a single shared instance
> (because
> it is already known to have good properties).  A less-desirable alternative
> is to used rng's seeded with different starting states - in this case the
> independence properties are not generally known.
>
> So I have some fairly deeply nested data structures (classes) that
> somewhere
> contain a reference to a RandomState object.
>
> I need to be able to clone these data structures, producing new independent
> copies, but I want the RandomState part to be the shared, singleton rs
> object.
>
> In python, no problem:
>
> ---
> from numpy.random import RandomState
>
> class shared_random_state (RandomState):
>     def __init__ (self, rs):
>         RandomState.__init__(self, rs)
>
>     def __deepcopy__ (self, memo):
>         return self
> ---
>
> Now I can copy.deepcopy the data structures, but the randomstate part is
> shared.  I just use
>
> rs = shared_random_state (random.RandomState(0))
>
> and provide this rs to all my other objects.  Pretty nice!
>
> --
> Those who fail to understand recursion are doomed to repeat it
>
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