[SciPy-User] Big performance hit when using frozen distributions on scipy 0.16.0

[Charles R Harris]

On Fri, Oct 28, 2016 at 10:53 AM, Nicolas Chopin <nicolas.chopin at ensae.fr>
wrote:

>  Hi list,
> I'm working on a package that does some complicate Monte Carlo
> experiments. The package passes around frozen distributions quite a lot.
> Trying to understand why certain parts were so slow, I did a bit of
> profiling, and stumbled upon this:
>
>  > %timeit x = scipy.stats.norm.rvs(size=1000)
> > 10000 loops, best of 3: 49.3 µs per loop
>
> > %timeit dist = scipy.stats.norm(); x = dist.rvs(size=1000)
> > 1000 loops, best of 3: 512 µs per loop
>
> So a x10 penalty when using a frozen dist, even if the size of the
> simulated vector is 1000. This is using scipy 0.16.0 on Ubuntu 16.04. I
> cannot replicate this problem on another machine with scipy 0.13.3 and
> Ubuntu 14.04 (there is a penalty, but it's much smaller).
>
> In the profiler, I can see that a lot of time is spent doing string
> operations (such as expand_tabs) in order to generate the doc. In the
> source, I see that this may depend on a certain -00 flag???
>

Did you try running with the -OO flag? Anyone know how well that works?

Chuck
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