Introduction to Sparse Matrices In Scilab - Projects

umf licenseumf ludelumf lufactumf lugetumf luinfoumf lusolveumfpackdisplay the umfpack licenseutility function used with umf lufactlu factorisation of a sparse matrixretrieve lu factors at the scilab levelget information on LU factorssolve a linear sparse system given the LU factorssolve sparse linear systemFigure 6 – Functions from the umfpack module.3 0 4 0 6;0 -1 -3 2 0;0 0 1 0 0;0 4 2 0 1];A = sparse ( Afull )b = [8 ; 45; -3; 3; 19];h = umf_lufact (A);x = umf_lusolve (h,b)umf_ludel (h);The previous script produces the following output.-->x = umf_lusolve (h,b)x =1.2.3.4.5.In the previous script, the variable h is a matrix handle, which containsinformations related to the sparse matrix. This is why it is necessary toexplicitely delete the matrix with the umf_ludel function. Indeed, if we donot delete the matrix handle, there is a loss of memory.7 The TAUCS packageThe TAUCS package provide several direct algorithms to compute Choleskydecompositions of sparse matrices. This package only manage symmetricpositive definite matrices. The algorithms also solve sparse linear systems18