These

"covariant and contravariant co ordinate systems"
"moving through different co ordinate systems"
"index-contraction system"

can mean a lot of different things in the context of a CAS. Some of
them are already implemented in sympy or numpy. For instance:

1. naive index contraction:

 - naive index contraction is implemented in numpy.einsum and can be
used with sympy through the dtype=object.
 - you can do naive index contraction also through the `tensor` module
in sympy, but it is destined to be used solely for code generation of
loops over n-dim arrays.

2. Actual tensor objects (i.e. geometrical objects) are implemented in
various ways in sympy:

 - the very new. very fast and very shiny tensor canonicalization
routines contributed by Pernici (for the xAct style of work, not yes
supporting explicit tensors)

 - for differential geometry see the `diffgeom` module: it is
coordinate system independent in the meaning that you write down your
objects explicitly in some coordinate systems, but you can mix
together bases and switch from one to another on-the-fly.

Please contribute to and clean up these modules, before you start
adding routines that are already partially implemented.

On 23 April 2013 21:03, F. B. <franz.bona...@gmail.com> wrote:
> I started working on such an implementation yesterday. It has already an
> index-contraction system. Give me some days to finish it, then I'll post it.
>
> This part is not only helpful, it is ESSENTIAL to all modern physics!
>
>
> On Tuesday, April 23, 2013 8:52:40 PM UTC+2, Amit wrote:
>>
>> Can the tensor implimentation related to covariant and contravariant co
>> ordinate systems and moving through different co ordinate systems be
>> helpful.I mean to say could covariant and contravariant transforms form the
>> basis for tensor module.Thanks.
>
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