gf_linsolve

Various linear system solvers.

# Calling Sequence

    X = gf_linsolve('gmres', spmat M, vec b[, int restart][, precond P][,'noisy'][,'res', r][,'maxiter', n])

    X = gf_linsolve('cg', spmat M, vec b [, precond P][,'noisy'][,'res', r][,'maxiter', n])

    X = gf_linsolve('bicgstab', spmat M, vec b [, precond P][,'noisy'][,'res', r][,'maxiter', n])

    {U, cond} = gf_linsolve('lu', spmat M, vec b)

    {U, cond} = gf_linsolve('superlu', spmat M, vec b)

## Description

Various linear system solvers.

## Command list

- `X = gf_linsolve('gmres', spmat M, vec b[, int restart][, precond 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.

- `X = gf_linsolve('cg', spmat M, vec b [, precond P][,'noisy'][,'res', r][,'maxiter', n])`

  Solve `M.X = b` with the conjugated gradient method. Optionally using `P` as preconditioner.

- `X = gf_linsolve('bicgstab', spmat M, vec b [, precond P][,'noisy'][,'res', r][,'maxiter', n])`

  Solve `M.X = b` with the bi-conjugated gradient stabilized method. Optionally using `P` as a preconditioner.

- `{U, cond} = gf_linsolve('lu', spmat M, vec b)`

  Alias for gf_linsolve('superlu',...)

- `{U, cond} = gf_linsolve('superlu', spmat M, vec b)`

  Solve `M.U = b` apply the SuperLU solver (sparse LU factorization). The condition number estimate `cond` is returned with the solution `U`.

## See Also

- getfem types

## Authors

Y. Collette