[Numpy-discussion] Choosing between NumPy and SciPy functions
ben.root at ou.edu
Fri Oct 31 11:07:03 EDT 2014
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
On Fri, Oct 31, 2014 at 10:26 AM, D. Michael McFarland <dmmcf at dmmcf.net>
> Stefan van der Walt <stefan at sun.ac.za> writes:
> > On 2014-10-27 15:26:58, D. Michael McFarland <dmmcf at 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.
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> NumPy-Discussion at scipy.org
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