Hello, when reading the draft, I've seen Elementwise multiplication is useful because it fits the common pattern for numerical code: it lets us easily and quickly perform a basic operation (scalar multiplication) on a large number of aligned values without writing a slow and cumbersome for loop. And this fits into a very general schema; e.g., in numpy, *all Python operators work elementwise on arrays of all dimensionalities.* Matrix multiplication is slightly more special-purpose -- it's only defined on 2d arrays, also known as "matrices" -- but still used very heavily across all application areas; mathematically, it's one of the most fundamental operations there is.
This is also the case in math so I do not think that it is a good argument. I really think that @ instead of * for scalar product is the good choice ! Don't forget the scientific math world which use more and more Python. Christophe BAL -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/CAAb4jGkT79_tErW-4sYbLvz0O%2BjQqWRpqSD5WHQyY9oA7Gr5_w%40mail.gmail.com. For more options, visit https://groups.google.com/d/optout.
