/**
* Uses LU decomposition to determine inverse
*/
public Matrix inverse_lu()
{
LUDecomposition lu = new LUDecomposition(this);
Matrix identity = new Matrix(this.cols, this.rows);
identity.setIdentity();
Matrix inverse = lu.solve(identity);
return(inverse);
}
public static void TestHarness()
{
// Matrix A = new Matrix(3, 3);
// A.setIdentity();
// A.data[0,1] = A.data[1,0] = 0.2;
// A.data[0,2] = A.data[2,0] = 0.3;
// A.data[1,2] = A.data[2,1] = 0.1;
// System.Console.WriteLine("A is\n{0}", A.dump());
//
// LUDecomposition A_lu = new LUDecomposition(A);
// System.Console.WriteLine("LU is\n{0}", A_lu.dump());
Matrix B = new Matrix(3, 3);
B.setIdentity();
B.data[0, 1] = B.data[1, 0] = 0.2;
B.data[0, 2] = B.data[2, 0] = 0.3;
B.data[1, 2] = 0.1;
B.data[2, 0] = 0.4;
Console.WriteLine("B is\n{0}", B.dump());
LUDecomposition B_lu = new LUDecomposition(B);
Console.WriteLine("LU is\n{0}", B_lu.dump());
Matrix b = new Matrix(3, 1);
b.data[0, 0] = 1.0;
b.data[1, 0] = 2.0;
b.data[2, 0] = 3.0;
Console.WriteLine("b is\n{0}", b.dump());
Matrix x = B_lu.solve(b);
Console.WriteLine("x is\n{0}", x.dump());
Matrix test_b = B.multiply(x);
Console.WriteLine("test_B is\n{0}", test_b.dump());
}
