On Sat, Mar 15, 2014 at 10:21 AM, Nathaniel Smith <n...@pobox.com> wrote: > On Fri, Mar 14, 2014 at 8:48 PM, William Stein <wst...@gmail.com> wrote: >> In retrospect, it appears that the OP should have asked the following >> question: From the perspective of Sage, if Python were to have >> another arithmetic operator (denoted @) with identical precedence >> rules to *, would we use it for anything? Would we extend the >> coercion model, etc.? Are there any algebraic structures at all that >> have two different "multiplications"? > > Indeed, this probably would have been the correct question, if only > I'd known! But the end result is that I learned a lot about how Sage > approaches things that I didn't know before, and the PEP got much > stronger from getting this feedback from a perspective I hadn't > understood before -- in fact I rewrote large parts of it in response > to comments here and on the sympy list. Thank you very much to > everyone who took the time to comment. > > The current status, in case anyone is curious, is that it looks like > '@' will in fact appear in Python 3.5, once some details are worked > out: > https://github.com/numpy/numpy/pull/4351#issuecomment-37717330 > If anyone here does have any opinions on those details then I'd love > to hear them. > >> His actual >> PEP had something claiming we had added something to the preparser, >> but that was not a multiplication operator, but simply a backslash >> shorthand for matrix inversion, like in Matlab, that nobody uses or >> cares about -- I just added it one day for fun in the early days -- >> based on no demand. > > Hmm, I don't remember saying this, and the text changed quite a bit > from what I originally sent around, but if you see any remaining > inaccuracies then please let me know so I can fix them! :-): > http://legacy.python.org/dev/peps/pep-0465/ > (In fact I know there's one inaccuracy in that version -- it says that > sage & sympy don't implement elementwise multiplication at all. My > local draft changes that to "Projects which currently use * for matrix > multiplication, and > which don't really care about elementwise multiplication at all", > which I think is closer to the truth?)
It's not that we don't care about elementwise multiplication of *arrays*, it's that we don't care about elementwise multiplication of *matrices* (and I've yet to find any use of the latter at all). I think the problem of numpy.matrix is http://en.wikipedia.org/wiki/Composition_over_inheritance There's currently only a single example (after much searching) where the two need to be mixed--an explicit conversion would be fine here. I am also opposed to this PEP as it singles out one (or two) special operators that behave differently than any other operator w.r.t. *not* being elementwise. The current behavior is much easier to understand. (I'm also not a fan of @ being both an operator and being used for decorators... but that's a different issue.) Also, this is not just about multiplication (or exponentiation). Note that for a matrix M and a scalar a the sum M + a is M + I a (where I is the identity matrix), again not elementwise. sage: import numpy as np sage: a = np.array([[1,2],[3,4]]) sage: a array([[1, 2], [3, 4]]) sage: a + 100 array([[101, 102], [103, 104]]) sage: M = matrix([[1,2],[3,4]]); M [1 2] [3 4] sage: M + 100 [101 2] [ 3 104] - Robert -- You received this message because you are subscribed to the Google Groups "sage-devel" group. To unsubscribe from this group and stop receiving emails from it, send an email to sage-devel+unsubscr...@googlegroups.com. To post to this group, send email to sage-devel@googlegroups.com. Visit this group at http://groups.google.com/group/sage-devel. For more options, visit https://groups.google.com/d/optout.
