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. -- You received this message because you are subscribed to the Google Groups "sympy" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/sympy?hl=en.
