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# umfpack

solve sparse linear system

### Calling Sequence

x = umfpack(A,"\",b) x = umfpack(b,"/",A)

### Arguments

- A
a sparse (real or complex) square matrix n x n

- b
in the first case, a column vector (n x 1) or a n x m matrix ; in the second case, a row vector (1 x n) or a m x n matrix

- x
in the first case , a column vector (n x 1) or a n x m matrix ; in the second case, a row vector (1 x n) or a m x n matrix

- 2d arg
string specifier "\" or "/"

### Description

This function is intended to work like the classic operators \ and / x = A\b and x = b/A) i.e. it solves a linear system Ax = b or xA = b with a sparse square (says n x n) real or complex matrix and with a compatible rhs b : n x m in the first case and m x n in the second.

### Details

First an LU factorisation of the matrix is computed (`P R^(-1) A Q = LU`

where P and Q are permutation matrices, R is a diagonal matrix (row scaling), L
a lower triangular matrix with a diagonal of 1, and U an upper triangular matrix)
then a first solution is computed with forward/backward subtitutions ;
finaly the solution is improved by iterative refinement.

### Examples

// this is the small linear test system from UMFPACK // whom solution must be [1;2;3;4;5] A = sparse( [ 2 3 0 0 0; 3 0 4 0 6; 0 -1 -3 2 0; 0 0 1 0 0; 0 4 2 0 1] ); b = [8 ; 45; -3; 3; 19]; x = umfpack(A,"\",b) // test the other form x A = b b = [8 20 13 6 17]; x = umfpack(b,"/",A) // solution must be [1 2 3 4 5] // test multiple rhs b = rand(5,3); x = umfpack(A,"\",b) norm(A*x - b) // test multiple rhs for x A = b b = rand(3,5); x = umfpack(b,"/",A) norm(x*A - b) // solve a complex system A = sparse( [ 2+%i 3+2*%i 0 0 0; 3-%i 0 4+%i 0 6-3*%i; 0 -1+%i -3+6*%i 2-%i 0; 0 0 1-5*%i 0 0; 0 4 2-%i 0 1] ); b = [ 3+13*%i ; 58+32*%i ; -19+13*%i ; 18-12*%i ; 22+16*%i ]; x = umfpack(A,"\",b) // x must be [1+i; 2+2i; 3+3i; 4 + 4i; 5+5i] // A benchmark of several linear solvers [A,descr,ref,mtype] = ReadHBSparse(SCI+"/modules/umfpack/examples/bcsstk24.rsa"); b = 0*ones(size(A,1),1); tic(); res = umfpack(A,'\',b); mprintf('\ntime needed to solve the system with umfpack: %.3f\n',toc()); tic(); res = linsolve(A,b); mprintf('\ntime needed to solve the system with linsolve: %.3f\n',toc()); tic(); res = A\b; mprintf('\ntime needed to solve the system with the backslash operator: %.3f\n',toc());

### See Also

- umf_lufact — lu factorisation of a sparse matrix
- umf_lusolve — solve a linear sparse system given the LU factors
- umf_ludel — utility function used with umf_lufact
- umf_luinfo — get information on LU factors
- umf_luget — retrieve lu factors at the Scilab level
- linsolve — linear equation solver
- backslash — (\) left matrix division.

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