On Sunday, March 9, 2014 7:20:50 PM UTC, Jeroen Demeyer wrote: > > I think the following piece should be made more clear, I don't > understand what you're trying to say here: > > The problem is that the presence of two different duck-types for numeric > data -- one where * means matrix multiply, and one where * means > elementwise multiplication -- make it impossible to write generic > functions that can operate on arbitrary data. >
Indeed, it's clear from everyone's responses here that I at least need to add a new section talking about these things explicitly, and also about why elementwise-* is actually used so often in practice in numeric computation (as opposed dto symbolic comptuation), and why np.matrix is so loathed. (It really is though, I didn't just make that up :-) I doubt you can find a single developer of any numpy-using package who has anything good to say about it.) I'll try to get to write such a section over the next few hours; at least it might make a better basis for discussion. In brief, the issue is that elementwise-* is a fine convention and you can use it to write useful code, and matrix-multiply-* is a fine convention and you can use it to write useful code, but if you then try to glue those two pieces of code together into a larger system you will quickly find yourself in hell as you have to cast objects back and forth at every function call. Or similarly, if you try to write a function that works regardless of whether it receives an elementwise-*-object or a matrix-multiply-*-object, then this is also very painful (suddenly you need lots of type-checking and if statements scattered around every single function you write, it's horrible and no-one is willing to do it). This doesn't get into the reasons why numpy goes with the elementwise-* convention, but it's why it seems important to have *some* convention. (Some of the reasons for why numpy goes with elementwise-* are here: https://github.com/njsmith/numpy/blob/matmul-pep/doc/neps/return-of-revenge-of-matmul-pep.rst#choice-of-operation ; the other important reason that that section doesn't talk about as much as it could is that numpy has n-dimensional arrays, while matrix multiplication is only really natural for 2d arrays.) -n -- 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.
