Thanks. I don't know how I missed sqrt(Matrix).
Yes, the specific context is solving hyperbolic systems of PDE's so the
matrices are small n-by-n were n is usually 2,3,4, or 5, but I have to do
it at points on a large 2D or 3D mesh so I'm looking for a nice way to
generate C or Fortran code for symbolic expressions of the form
A^{-1}*B^{-1/2} where A is SPD and B is symmetric with non-negative
eigenvalues. There may be a point when I'm better off computing these with
lapack factorizations, but I'd like to have sympy-generated analytical
expressions
Chris
On Thu, Oct 2, 2014 at 7:14 PM, Aaron Meurer <[email protected]> wrote:
> SymPy can do it, as long as it can compute the roots of the
> characteristic polynomial. Is there any specific use-case you're
> looking for? The syntax is Matrix.diagonalize (or sqrt(Matrix) if all
> you want is the square root).
>
> Aaron Meurer
>
> On Thu, Oct 2, 2014 at 6:54 PM, Chris Kees <[email protected]> wrote:
> > Hi,
> >
> > Does anybody have suggestions on sympy examples for symbolic eigenvector
> > decompositions A=RDR^t where A is symmetric with real positive distinct
> > eigenvalues? Or more specifically symbolic computations of A^{-1/2}.
> >
> > Chris
> >
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