Eigen values of a Matrix with symbols

[Sankaranarayanan S]

I need to find eigen values of matrix with symbols (sx) for the solution of an optimization problem. It seems there is no direct way to do it. numpy.linalg.* does not seem to work for symbolic matrices. Is there anyway to get the eigen values without doing a direct implementation. Thank you

[Joel Andersson]

Puh... a symbolic expressions for the all the eigenvalues?  Do you need all the eigenvalues or just the largest/smallest one (which can be expressed as a 2-norm)? What does the optimization problem look like and how do the eigenvalues enter? Maybe you can express it as a semi-definite program?

Regards,

Joel

[Sankaranarayanan S]

Hi Joel,
Thanks for the reply. I just need the maximum Eigen value to find an outer bound which then enters the constraint. I could very well use the 2-norm. Thank you.
Regards,
Sankar

[Marco Vaccari]

Hi, I came across this old post because I have the same problem that Sankar had. 
Since the norm_2 is used only for vector and norm_fro(A) has no direct relation to the maximum eigenvalue of matrix A, how can I calculate the spectral radius of A (square matrix with SX coefficients?

Thanks,

Marco