On Sat, Mar 15, 2014 at 3:29 PM, Nathaniel Smith <n...@pobox.com> wrote:
> > It would be nice if u@v@None, or some such, would evaluate as a dyad. > Or else we will still need the concept of row and column 1-D matrices. I > still think v.T should set a flag so that one can distinguish u@v.T(dyad) > from u.T@v(inner product), where 1-D arrays are normally treated as column > vectors. > > This sounds important but I have no idea what any of it means :-) (What's > a dyadic matrix?) Can you elaborate? > I assume dyadic means 2d. This discussion gave me an idea that is only tangentially relevant to the discussion at hand. It looks like numpy operators commonly need to make a choice whether to treat an Nd array as a unit (atom) or as a list to broadcast itself over. APL-derived languages solve this problem by using operator modifiers. Applied to our case, given a dot-product operator @, each[@] operator works on 2d arrays by "dotting" them pair-wise and returning a 1d array. Similarly, eachleft[@] would operate on 2d, 1d operands by broadcasting itself over the left operand (incidentally reproducing the mat @ vec behavior) and eachright[@] would treat its left operand atomically and broadcast over the right operand. My idea is inspired by Guido's "use facade" suggestion. We can define ndarray.each(axes=(0,)) method that would return a light-weigh proxy object so that a each[@] b is spelled a.each() @ b.each() a eachleft[@] b is spelled a.each() @ b a eachright[@] b is spelled a @ b.each()
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