> It seems to me that A(m0, m1, m2)[2,0, 1] and A(F(2), F(0), F(1)) are > equivalent representations; e.g. > A(-m0, m1, m2)[2,0, 1] corresponds to A(-F(2), F(0), F(1)), etc. > I do not like A(m0, m1, m2)[2,0, 1]; I do not think it is standard > notation. >
A(m0, m1, m2)[2,0, 1] will be the extraction of an element from a numpy ndarray associated to the tensor (if any). A(-F(2), F(0), F(1)) instead corresponds to the abstract tensor with numerical indices specified. The first one, A(m0, m1, m2)[2,0, 1], will not be a tensor expression at all (like the element of a matrix is not a matrix), while the second one keeps being a tensor. You notice that there could be contradictions like: A(m0, F(1), -F(2))[2,0, 1] ===> one should think how to make both ways work together. -- 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. For more options, visit https://groups.google.com/groups/opt_out.
