> On 16/04/2008, Alan G Isaac <[EMAIL PROTECTED]> wrote: >> The rule is: >> to get a submatrix, >> use multiple indices.
On Wed, 16 Apr 2008, Stéfan van der Walt wrote: > That is not the rule for arrays; you argued the compatibility point yourself. Sorry, I do not understand. I am saying only: I propose no change in current matrix behavior in response to nonscalar indexes. On Wed, 16 Apr 2008, Stéfan van der Walt wrote: > Are you opposed to fixing the problem the way Tim > suggested? It seems lots of complexity for a payoff I do not see. My proposal is simpler and stays closer to ndarray behavior. But having a matrix be a container of such "RowVectors" is better than the current behavior. I do not see that it gets in the way of anything desirable, as long as the array attribute of your "vectors" will return a 1d array. > Why would linear algebra users prefer 1d arrays instead of vectors? What is a "vector"? To me a vector is an element of a vector space. As far as I can tell, a 1d array *is* a vector. If you mean by "vector" what people mean when they say "row vector" or "column vector", this is just short hand for special matrices. If I want these special matrices, I can have them right now. Of course I cannot index the elements with a scalar... Cheers, Alan Isaac _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
