Just to throw in my two cents here. I feel that sometimes, features are tried out first elsewhere (possibly in scipy) and then brought down into numpy after sufficient shakedown time. So, in some cases, I wonder if the numpy version is actually more refined than the scipy version? Of course, there is no way to know this from the documentation, which is a problem. Didn't scipy have nanmean() for a while before Numpy added it in version 1.8?
Ben Root On Fri, Oct 31, 2014 at 10:26 AM, D. Michael McFarland <dm...@dmmcf.net> wrote: > Stefan van der Walt <ste...@sun.ac.za> writes: > > > On 2014-10-27 15:26:58, D. Michael McFarland <dm...@dmmcf.net> wrote: > >> What I would like to ask about is the situation this illustrates, where > >> both NumPy and SciPy provide similar functionality (sometimes identical, > >> to judge by the documentation). Is there some guidance on which is to > >> be preferred? > > > > I'm not sure if you've received an answer to your question so far. My > > advice: use the SciPy functions. SciPy is often built on more extensive > > Fortran libraries not available during NumPy compilation, and I am not > > aware of any cases where a function in NumPy is faster or more extensive > > than the equivalent in SciPy. > > The whole thread has been interesting reading (now that I've finally > come back to it...got busy for a few days), but this is the sort of > answer I was hoping for. Thank you. > > Best, > Michael > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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