Math 5610 - Computational Linear Algebra


Project maintained by BrandonFurman Hosted on GitHub Pages — Theme by mattgraham

Software Manual

Routine Name: slowSquareSystemSolver

Author: Brandon Furman

Language: C++

Description/Purpose: This function solves the square linear system of equations Ax = b using Gaussian Elimination. To do so it utilizes the matRowReduction and augMatBackSub functions.

Input: This function requires a coefficient matrix, A, in the form of an array2D object and a vector of constant terms, b, in the form of a array1D object. The coefficient matrix should have a nonzero entries for all of its diagonal elements. If there are zero entries, an exception will be thrown.

Output: The function returns a array1D object that is the solution to the linear system of equations.

Usage/Example: An example of the usage of this function can be found below for the problem where A = [[1,2,3],[5,6,7],[11,9,11]] and b = [6,1,9].

int m, n, l;
m = 3; n = 3; l = 3;

//Create and populate the coefficient matrix.
array2D A;
A.allocateMem(m, n);
A(0, 0) = 1; A(0, 1) = 2; A(0, 2) = 3;
A(1, 0) = 5; A(1, 1) = 6; A(1, 2) = 7;
A(2, 0) = 11; A(2, 1) = 9; A(2, 2) = 11;

//Create and populate the vector of constant terms.
array1D b;
b.allocateMem(n);
b(0) = 6; b(1) = 1; b(2) = 9;

//Use Gauss Elimination to solver the linear system.
array1D x;
x = slowSquareSystemSolver(A,b);

//Print the results.
for (int i = 0; i < l; i++) {
	std::cout << x(i) << " ";
}

This code outputs the following to the console:

0.8125 -11.375 9.3125

which is the exact solution of the stated problem.

Implementation/Code: The SquareSystemSolver() function is implemented as follows:

array1D slowSquareSystemSolver(array2D& A, array1D& b) {

	int m = A.getRows();
	int n = A.getCols();
	int l = b.getLength();

	if (m != n || m != l) {
		throw "slowSquareSystemSolver: Incompatible Sizes";
	}

	array1D sol;
	array2D augMat;

	//Allocate memory for the augmented matrix.
	//We need an additional column to account 
	//for the constant terms.
	augMat.allocateMem(m, n + 1);

	//Compose the augmented matrix using the
	//coefficient matrix and constant terms.
	for (int i = 0; i < m; i++) {
		for (int j = 0; j < n; j++) {
			augMat(i, j) = A(i, j);
		}
		augMat(i, n) = b(i);
	}

	//Perform row reduction on the
	//augmented matrix.
	augMat = matRowReduction(augMat);

	//Perform back substitution on
	//the row reduced matrix to get
	//the final solution.
	sol = augMatBackSub(augMat);

	return sol;
}

Last Modified: March/2019