Please send the code. This should work fine.

  Barry


> On Jun 25, 2020, at 2:43 PM, Rakesh Halder <[email protected]> wrote:
> 
> Hi all,
> 
> I'm using PETSc for matrix calculations as part of a model order reduction 
> code. An algorithm I'm using requires that I compute the explicit inverse of 
> a matrix, as it needs to be used in matrix-matrix products. 
> 
> The matrix is small (I'll show a 5x5 example), and I first find the LU 
> factorization of it as follows:
> 
>   MatGetOrdering(A,MATORDERINGNATURAL,&perm,&iperm);
>   MatFactorInfoInitialize(&info);
>   MatLUFactor(A,perm,iperm,&info);
> 
> I then find the inverse of it:
> 
>   MatMatSolve(A,I,B);
> 
> Where I is the identity matrix, and B is the inverse. The subroutine does 
> calculate an inverse, although not accurately; the matrix A I looked at is:
> 
> 5.23E-02      1.86E-02        2.67E-02        4.58E-02        3.55E-02
> 6.37E-03      5.86E-02        5.07E-03        1.64E-02        1.36E-02
> -4.07E-02     3.99E-03        5.50E-02        1.77E-02        -3.21E-02
> 1.96E-02      -5.53E-03       4.02E-02        -5.37E-02       1.80E-02
> 1.51E-02      1.70E-02        -1.57E-02       -3.75E-03       -5.64E-02
> 
> And when I take the product A*B, I don't recover the identity matrix, but 
> rather:
> 
> 9.97E-01      2.77E-04        -1.66E-03       1.25E-04        -1.10E-03
> -6.79E-04     9.99E-01        -1.72E-04       6.24E-04        1.16E-03
> 2.70E-03      -3.98E-04       9.98E-01        -1.51E-04       6.82E-04
> -3.35E-04     -4.82E-04       -1.03E-03       9.99E-01        9.80E-05
> -9.50E-04     -8.70E-04       8.37E-04        -3.68E-04       9.99E-01
> 
> I believe this is causing large inaccuracies in my program, as the diagonal 
> and off-diagonal entries have large errors associated with them. I am 
> wondering if there is a way to perhaps tighten the tolerance of the 
> subroutine, or if there are other methods I can use. I would like to avoid 
> using KSP and solving for the inverse vector-by-vector if possible.
> 
> Thanks,
> 
> Rakesh Halder

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