Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function
taucs_chinfo
get information on Cholesky factors
Calling Sequence
[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
OK
is%t
ifC_ptr
is a valid pointer to an Cholesky factorization (and%f
else)if
OK
is%t
thenn
andcnz
are respectively the matrix order and the number of non zeros elements in the supernodal structure storingC
; ifOK
is%f
,n
andcnz
are 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 mesure 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/examples/bcsstk24.rsa"); // compute the factorisation Cp = taucs_chfact(A); [OK, n, cnz]=taucs_chinfo(Cp)
See Also
- taucs_chfact — cholesky factorisation of a sparse s.p.d. matrix
- taucs_chsolve — solve a linear sparse (s.p.d.) system given the Cholesky factors
- taucs_chdel — utility function used with taucs_chfact
- taucs_chget — retrieve the Cholesky factorization at the scilab level
Report an issue | ||
<< taucs_chget | UMFPACK Interface (sparse) | taucs_chsolve >> |