Module linsolve

linsolve_gmres(M, b, restart=None, *args)

Synopsis: X = linsolve_gmres(SpMat M, vec b[, int restart][, Mrecond P][,’noisy’][,’res’, r][,’maxiter’, n])

Solve M.X = b with the generalized minimum residuals method.

Optionally using P as preconditioner. The default value of the restart parameter is 50.

linsolve_cg(M, b, P=None, *args)

Synopsis: X = linsolve_cg(SpMat M, vec b [, Mrecond P][,’noisy’][,’res’, r][,’maxiter’, n])

Solve M.X = b with the conjugated gradient method.

Optionally using P as preconditioner.

linsolve_bicgstab(M, b, P=None, *args)

Synopsis: X = linsolve_bicgstab(SpMat M, vec b [, Mrecond P][,’noisy’][,’res’, r][,’maxiter’, n])

Solve M.X = b with the bi-conjugated gradient stabilized method.

Optionally using P as a preconditioner.

linsolve_lu(M, b)

Alias for gf_linsolve(‘superlu’,...)

linsolve_superlu(M, b)

Solve M.U = b apply the SuperLU solver (sparse LU factorization).

The condition number estimate cond is returned with the solution U.

linsolve_mumps(M, b)

Solve M.U = b using the MUMPS solver.