[Numpy-discussion] Proposal: numpy.random.random_seed

[Robert Kern]

On Tue, May 17, 2016 at 4:54 AM, Stephan Hoyer <shoyer at gmail.com> wrote:
>
> I have recently encountered several use cases for randomly generate
random number seeds:
>
> 1. When writing a library of stochastic functions that take a seed as an
input argument, and some of these functions call multiple other such
stochastic functions. Dask is one such example [1].

Can you clarify the use case here? I don't really know what you are doing
here, but I'm pretty sure this is not the right approach.

> 2. When a library needs to produce results that are reproducible after
calling numpy.random.seed, but that do not want to use the functions in
numpy.random directly. This came up recently in a pandas pull request [2],
because we want to allow using RandomState objects as an alternative to
global state in numpy.random. A major advantage of this approach is that it
provides an obvious alternative to reusing the private numpy.random._mtrand
[3].

It's only pseudo-private. This is an authorized use of it.

However, for this case, I usually just pass around the the numpy.random
module itself and let duck-typing take care of the rest.

> [3] On a side note, if there's no longer a good reason to keep this
object private, perhaps we should expose it in our public API. It would
certainly be useful -- scikit-learn is already using it (see links in the
pandas PR above).

Adding a public get_global_random_state() function might be in order.
Originally, I wanted there to be *some* barrier to entry, but just grabbing
it to use as a default RandomState object is definitely an intended use of
it. It's not going to disappear.

--
Robert Kern
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