Hi, On Thu, Apr 4, 2013 at 9:21 AM, Chris Barker - NOAA Federal <chris.bar...@noaa.gov> wrote: > On Wed, Apr 3, 2013 at 6:13 PM, Matthew Brett <matthew.br...@gmail.com> wrote: >>> We all agree that 'order' is used with two different and orthogonal >>> meanings in numpy. > > well, not entirely orthogonal -- they are the some concept, used in > different contexts, so there is some benefit to their having > similarity. So I"d advocate for using the same flag names in any case > -- i.e. "C" and "F" in both cases. > >>> I think we are now more or less agreeing that: >>> >>> np.reshape(a, (3, 4), index_order='F') >>> >>> is at least as clear as: >>> >>> np.reshape(a, (3, 4), order='F') > > sure. > > The trick is: > > np.reshape(a, (3, 4), index_order='A') > > which in mingling index_order and memory order...... > >> I believe our job here is to come to some consensus. > > yup. > >> In that spirit, I think we do agree on these statements above. > > with the caveats I just added... > >> Now we have the cost / benefit. >> >> Benefit : Some people may find it easier to understand numpy when >> these constructs are separated. >> >> Cost : There might be some confusion because we have changed the >> default keywords. >> >> Benefit >> ----------- >> >> What proportion of people would find it easier to understand with the >> order constructs separated? > > It's not just numbers -- it's depth of confusion -- if, once you "get" > it, you remember it for the rest of your numpy use, then it's not big > deal. However, if you need to re-think and test every time you > re-visit reshape or ravel, then there's a significant benefit. > > We are talking about "separating the concepts", but I think it takes > more than a keyword change to do that -- the 'A' and 'K' flags mingle > the concpets, and are going to be confusing with new keywords -- maybe > even more so (it says index_order, but the docstring talks about > memory order) > > Does anyone think we should depreciate the 'A' and 'K' flags?
Would you consider moving this one to another thread? Cheers, Matthew _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
