bicg1 cg1 coo_csr csr_coo csr_dense csr_dusmm csr_dusmv csr_dussm csr_dussv csr_ssr csr_trans dense_csr ssr_csr ssr_dusmv

bicg1() def bicg1 ( n  , val  , rowptr  , colind  , b  , x  , tol  = 1.0e-10, maxiter  = 500  ) Solution of linear system Ax = b using bi-conjugate gradient (BICG) method (Simple driver) Purpose This routine solves the linear system Ax = b using the bi-conjugate gradient (BICG) iterative method. Matrix A is represented in CSR format. Returns (info, iter, res) info (int): = 0: Successful exit. = i < 0: The (-i)-th argument is invalid. = 11: Maximum number of iterations exceeded. = 12: Breakdown occurred. iter (int): Final number of iterations. res (float): Final residual norm norm(b - A*x). Parameters [in] n Dimension of the matrix. (n >= 0) (If n = 0, returns without computation) [in] val Numpy ndarray (1-dimensional, float, nnz) Values of nonzero elements of matrix A (where nnz is the number of nonzero elements). [in] rowptr Numpy ndarray (1-dimensional, int32, n + 1) Row pointers of matrix A. [in] colind Numpy ndarray (1-dimensional, int32, nnz) Column indices of matrix A (where nnz is the number of nonzero elements). [in] b Numpy ndarray (1-dimensional, float, n) Right hand side vector b. [in,out] x Numpy ndarray (1-dimensional, float, n) [in] Initial guess of solution. [out] Obtained approximate solution. [in] tol (Optional) Tolerance for convergence test. (default = 1.0e-10) Assumed to be converged if norm(b - A*x) <= tol*norm(b). If tol < eps (machine epsilon), tol = eps is assumed. [in] maxiter (Optional) Maximum number of iterations. (maxiter > 0) (default = 500)