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 > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion > _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
