Sparse Matrix Algorithms |
Example: Minimum Residual Algorithm |
For symmetric indefinite matrices it is best to use the minimum residual algorithm. The following example is slightly modified from the previous example by negating the first matrix element:
/* minimum residual algorithm */ /* value row col */ A = { -3 1 1, 1 2 1, 4 2 2, 1 3 2, 3 4 2, 10 3 3, 3 4 4 }; /* right-hand sides b = (1 1 1 1) */ b = {1, 1, 1, 1}; /* desired solution tolerance (optional) */ tol = 1e-7; /* maximum number of iterations (optional) */ maxit = 200; /* allocate iteration progress (optional) */ hist = j(50, 1); /* initial guess (optional) */ start = {2, 3, 4, 5}; /* invoke minimum residual method */ call itsolver ( x, st, it, /* output parameters */ 'minres', a, b, 'ic', /* input parameters */ tol, /* optional control parameters */ maxit, start, hist ); print x; /* print solution */ print st; /* print solution tolerance */ print it; /* print resultant number of iterations */
X -0.27027 0.1891892 0.0810811 0.1441441 ST 1.283E-15 IT 4
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