% You can use the following matrices to test your eigensolver
% implementations.
%
% Change to the format for whichever language you're using
% (don't write a reader function).
% 
% For the report, you don't need to show results for all 6,
% but I suggest showing result for Aj with the largest j
% that works, and the first j (if any) that fails. This will
% show what your implementation can handle and what it can
% not. 

% A1-A3 should work with any implementation
A1   = [1,3; 3,1];
eigvals1 = [4,-2];

A2   = [3,1;1,3];
eigvals2 = [4,2];

A3   = [1,2,3; 4,3.141592653589793,6; 7,8,2.718281828459045];
eigvals3 = [12.298958390970709, -4.4805737703355,  -0.9585101385863923];

% A4-A5 require the method to be robust for singular matrices 
A4   = [1,2,3; 4,5,6; 7,8,9];
eigvals4 = [16.1168439698070429897759172023, -1.11684396980704298977591720233, 0];

A5   = [1,2,3,4,5; 6,7,8,9,10; 11,12,13,14,15; 16,17,18,19,20],[21,22,23,24,25];
eigvals5 = [68.6420807370024007587203237318, -3.64208073700240075872032373182, 0, 0, 0];

% A6 has eigenvalue with multiplicity and is singular
A6  = [1.962138439537238,0.03219117137713706,0.083862817159563,-0.155700691654753,0.0707033370776169;
       0.03219117137713706, 0.8407278248542023, 0.689810816078236, 0.23401692081963357, -0.6655765501236198; 
       0.0838628171595628, 0.689810816078236,   1.3024568091833602, 0.2765334214968566, 0.25051808693319155;  
       -0.1557006916547532, 0.23401692081963357, 0.2765334214968566, 1.3505754332321778, 0.3451234157557794; 
       0.07070333707761689, -0.6655765501236198, 0.25051808693319155, 0.3451234157557794, 1.5441014931930226];
eigvals6 = [2,2,2,1,0];




