Please note that the recommended version of Scilab is 6.0.0. This page might be outdated.
See the recommended documentation of this function
solve a linear sparse (s.p.d.) system given the Cholesky factors
[x] = taucs_chsolve(C_ptr, b [, A])
a pointer to a handle of the Cholesky factors (C,p with A(p,p)=CC')
a real column vector or a matrix (multiple rhs)
a real column vector or a matrix in case of multiple rhs ( x(:,i) is solution of A x(:,i) = b(:,i))
(optional) the real s.p.d. matrix A (to use for iterative refinement step)
This function must be used in conjonction with taucs_chfact which
computes the Cholesky factorization of a sparse real s.p.d. matrix.
When the matrix
A is provided, one iterative refinement
step is done (the refined solution is accepted if it improves the
2-norm of the residual
Like in taucs_chfact the matrix A may be provided either in its complete form (that is with the lower triangle also) or only with its upper triangle.
see the example section of taucs_chfact
- taucs_chfact — cholesky factorisation of a sparse s.p.d. matrix
- taucs_chdel — utility function used with taucs_chfact
- taucs_chinfo — get information on Cholesky factors
- taucs_chget — retrieve the Cholesky factorization at the scilab level
- cond2sp — computes an approximation of the 2-norm condition number of a s.p.d. sparse matrix
- taucs by Sivan Toledo (see taucs_license)
- scilab interface by Bruno Pincon