On 3/27/07, Zachary Pincus <[EMAIL PROTECTED]> wrote:
So we are left with the current behavior: (a) M[i,:] is a matrix. (b) M[i] is a matrix. (c) Iteration over M yields matrices.
I find it useful if M[i] indexes the matrix interpreted as a column-vector (vec(M), or M(:) in Matlab notation), e.g., you could pick out the diagonal as M[::n+1], or if N is an index-set of certain elements in M, then you could access those elements as M[N]. Then I would also say that iterating over a matrix should just return the elements of vec(M) one by one. In general, I think the Matlab notation works well: * M[I,J] where I and J and index-sets returns a len(I) x len(J) matrix * M[I] returns a len(I) vector (a column or row vector depending on orientation of I) The index-sets could be a single integer, a list, or a slice. But I can see there are good arguments for using the NumPy conventions as well...
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