Hi, On Thu, Apr 25, 2013 at 10:42 AM, Robert Kern <[email protected]> wrote: > On Thu, Apr 25, 2013 at 6:30 PM, Matthew Brett <[email protected]> > wrote: >> Hi, >> >> On Thu, Apr 25, 2013 at 10:14 AM, Robert Kern <[email protected]> wrote: >>> On Wed, Apr 24, 2013 at 10:37 PM, andrew giessel >>> <[email protected]> wrote: >>>> Hello all- >>>> >>>> A while back I emailed the list about function for the numpy namespace, >>>> iteraxis(), which allows you to generalize the default iteration behavior >>>> of >>>> numpy arrays over any axis. >>>> >>>> I've implemented this function more cleanly and the pull request is here: >>>> https://github.com/numpy/numpy/pull/3262, and includes passing tests and >>>> documentation. >>>> >>>> This is very simple code, which uses np.rollaxis() to bring the desired >>>> dimension to the front, and then allows you to loop over slices in this >>>> re-structured view of the array. While little more than an alias, I feel >>>> this is a very useful function because looping over iterators is a core >>>> pattern in python, and makes working with slices of any multidimensional >>>> array very pythonic. Adding this function makes this more visible for >>>> users, new and old, and I hope members of this list will agree it is worth >>>> adding to the namespace. >>> >>> I'm afraid I don't. It's a just a reduced-functionality version of >>> rollaxis(). I don't think the additional name adds anything >>> substantial. >> >> There's a little more on this in the pull request discussion for those >> of y'all that are interested. >> >> So the decision has to be based on some estimate of: >> >> 1) Cost for adding a new function to the namespace >> 2) Benefit : some combination of: Likelihood of needing to iterate >> over arbitrary axis. Likelihood of not finding rollaxis / transpose as >> a solution to this. Increased likelihood of finding iteraxis in this >> situation. > > 3) Comparison with other solutions that might obtain the same benefits > without the attendant costs: i.e. additional documentation in any > number of forms.
Right, good point. That would also need to be weighted with the likelihood that people will find and read that documentation. Cheers, Matthew _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
