Comment #12 on issue 1268 by [email protected]: allow lambdify to take  
vectors and matrices are arguments
http://code.google.com/p/sympy/issues/detail?id=1268

I have to figure out the sympy rules for sympy.Matrix indexing, slicing, and
broadcasting before I can go any further with anything other than  
DeferredVector.
(For DeferredVector, these issues seem to have obvious solutions.)

As a user quite familiar with numpy.ndarray, I would use that as my  
reference for
"obvious" behavior for the N-dimensional case, but numpy.ndarray differs  
from
numpy.matrix in indexing and slicing, and I'm afraid I haven't used  
numpy.matrix or
sympy.Matrix particularly much to understand the behavior there. (I  
understand there
is a desire to keep a similar behavior between sympy.Matrix and  
numpy.matrix.)

Thus, for me to move forward with anything other than DeferredVector, I  
feel I have
to come to at least an understanding of the desired behavior of  
sympy.Matrix and then
attempt to emulate it.

Also, I didn't consider Tensor until you just raised it. Which, to be  
honest, makes
these issues seem more daunting. In fact, a sympy.DeferredNDArray modeled  
after
numpy.ndarray would be a lot easier for me to think about, as that is part  
of my
familiar set of daily-use tools.

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