Hi,

In sympy.physics.quantum we use sympy Matrix instances all over the
place.  These can be quite large (100x100 up to many 1000x1000.  In
the future we could get even bigger) and always have symbolic entries.
 At times we do like to convert them to numerical numpy arrays, but in
many cases we really want the symbolic forms.

On Sat, May 28, 2011 at 6:56 AM, SherjilOzair <sherjiloz...@gmail.com> wrote:
> I would like to know how and where Sympy's matrices are used.
> Is Sympy matrices used for numeric computing anywhere ?
> Are Sympy Matrices expected to offer any advantage that matrices in
> numpy/scipy or other libraries cannot offer ?
>
> Is its use limited to symbolic ? What size of Matrices with symbolic
> content is used ?
> Operations on Expr are way costlier than operations on numerics. So,
> knowing the size of the symbolic matrices that are required would help
> me in optimization when writing algorithms for sparse matrices, and
> also when refactoring Matrix.
>
> I expect that one cannot use too large symbolic matrices, as solving/
> inversing/etc. would result in expression blowup.
>
> I would be glad if you could also tell what running time you would
> expect from the matrices that you use.

instant ;)

When we are dealing with large symbolic matrices, we are typically
just doing matrix/vector multplies.  But for small matrices we do
other things like linear solves, decompositions and eigenvalue
problems.  symbolic eigenvalues are great, but expressions quickly get
out of hand as the matrix size increases.

Cheers,

Brian

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-- 
Brian E. Granger
Cal Poly State University, San Luis Obispo
bgran...@calpoly.edu and elliso...@gmail.com

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