Please note that the recommended version of Scilab is 2026.0.0. This page might be outdated.
See the recommended documentation of this function
taucs_chinfo
get information on Cholesky factors
Syntax
[OK, n, cnz] = taucs_chinfo(C_ptr)
Arguments
- C_ptr
- a pointer to a Cholesky factorization 
- OK
- a scalar boolean 
- n
- a scalar integer 
- cnz
- a scalar integer 
Description
This function may be used to know basic information about the Cholesky factor created with taucs_chfact :
- first - OKis- %tif- C_ptris a valid pointer to an Cholesky factorization (and- %felse)
- if - OKis- %tthen- nand- cnzare respectively the matrix order and the number of non zeros elements in the supernodal structure storing- C; if- OKis- %f,- nand- cnzare set to the void matrix [].
Details
Due to the supernodal structure used for C, cnz is larger
            than the exact number of non-zeros elements in C (and so this cnz
            is a measure of the memory used internally). To get the exact cnz you may retrieve
            the Cholesky factor with taucs_chget then apply
            the nnz scilab function (see the 2d example in taucs_chget).
Examples
// Example #1 : a small linear test system // whom solution must be [1;2;3;4;5] A = sparse( [ 2 -1 0 0 0; -1 2 -1 0 0; 0 -1 2 -1 0; 0 0 -1 2 -1; 0 0 0 -1 2] ); b = [0 ; 0; 0; 0; 6]; Cp = taucs_chfact(A); [OK, n, cnz]=taucs_chinfo(Cp)
// Example #2 a real example // first load a sparse matrix [A] = ReadHBSparse(SCI+"/modules/umfpack/demos/bcsstk24.rsa"); // compute the factorization Cp = taucs_chfact(A); [OK, n, cnz]=taucs_chinfo(Cp)
See also
- taucs_chfact — cholesky factorization of a sparse s.p.d. matrix
- taucs_chsolve — solves a linear s.p.d. system A*X = B from Cholesky factors of the sparse A
- taucs_chdel — utility function used with taucs_chfact
- taucs_chget — retrieve the Cholesky factorization at the scilab level
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