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rafiter
(obsolete) iterative refinement for a s.p.d. linear system
Calling Sequence
[xn, rn] = rafiter(A, C_ptr, b, x0, [, nb_iter, verb])
Arguments
- A
a real symmetric positive definite sparse matrix
- C_ptr
a pointer to a Cholesky factorization (got with taucs_chfact)
- b
column vector (r.h.s of the linear system) but "matrix" (multiple r.h.s.) are allowed.
- x0
first solution obtained with taucs_chsolve(C_ptr, b)
- nb_iter
(optional) number of raffinement iterations (default 2)
- verb
(optional) boolean, must be %t for displaying the intermediary results, and %f (default) if you do not want.
- xn
new refined solution
- rn
residual (
A*xn - b)
Description
This function is somewhat obsolete, use x = taucs_chsolve(C_ptr,b,A)
(see taucs_chsolve) which do one iterative refinement step.
To use if you want to improve a little the solution got with taucs_chsolve. Note that with verb=%t the displayed internal steps are essentially meaningful in the case where b is a column vector.
Caution
Currently there is no verification for the input parameters !
Examples
[A] = ReadHBSparse(SCI+"/modules/umfpack/examples/bcsstk24.rsa"); C_ptr = taucs_chfact(A); b = rand(size(A,1),1); x0 = taucs_chsolve(C_ptr, b); norm(A*x0 - b) [xn, rn] = rafiter(A, C_ptr, b, x0, verb=%t); norm(A*xn - b) taucs_chdel(C_ptr)
See Also
Authors
Bruno Pincon <Bruno.Pincon@iecn.u-nancy.fr>
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