[Numpy-discussion] Vectorized percentile function in Numpy (PR #2970)
Sebastian Berg
sebastian@sipsolutions....
Tue Apr 23 17:16:50 CDT 2013
On Tue, 2013-04-23 at 12:13 -0500, Jonathan Helmus wrote:
> Back in December it was pointed out on the scipy-user list[1] that
> numpy has a percentile function which has similar functionality to
> scipy's stats.scoreatpercentile. I've been trying to harmonize these
> two functions into a single version which has the features of both.
> Scipy PR 374[2] introduced a version which look the parameters from
> both the scipy and numpy percentile function and was accepted into Scipy
> with the plan that it would be depreciated when a similar function was
> introduced into Numpy. Then I moved to enhancing the Numpy version with
> Pull Request 2970 [3]. With some input from Sebastian Berg the
> percentile function was rewritten with further vectorization, but
> neither of us felt fully comfortable with the final product. Can
> someone look at implementation in the PR and suggest what should be done
> from here?
>
Thanks! For me the main question is the vectorized usage when both
haystack (`a`) and needle (`q`) are vectorized. What I mean is for:
np.percentile(np.random.randn(n1, n2, N), [25., 50., 75.], axis=-1)
I would probably expect an output shape of (n1, n2, 3), but currently
you will get the needle dimensions first, because it is roughly the same
as
[np.percentile(np.random.randn(n1, n2, N), q, axis=-1) for q in [25., 50., 75.]]
so for the (probably rare) vectorization of both `a` and `q`, would it
be preferable to do some kind of long term behaviour change, or just put
the dimensions in `q` first, which should be compatible to the current
list?
Regards,
Sebastian
> Cheers,
>
> - Jonathan Helmus
>
>
> [1] http://thread.gmane.org/gmane.comp.python.scientific.user/33331
> [2] https://github.com/scipy/scipy/pull/374
> [3] https://github.com/numpy/numpy/pull/2970
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
More information about the NumPy-Discussion
mailing list