public void QRAlgorithmComputeEigenvaluesTest()
{
for (Int32 matrixIndex = 0; matrixIndex < this.matrices.Length; matrixIndex++)
{
Double[] result = QRAlgorithm.ComputeEigenvalues(this.matrices[matrixIndex]).ToArray();
result.ShouldBe(this.expectedEigenvalues[matrixIndex], 0.001);
}
}
public void QRAlgorithmComputeEigenvectorsTest()
{
for (Int32 matrixIndex = 0; matrixIndex < this.matrices.Length; matrixIndex++)
{
Vector[] result = QRAlgorithm.ComputeEigenvectors(this.matrices[matrixIndex]).ToArray();
for (Int32 vectorIndex = 0; vectorIndex < result.Length; vectorIndex++)
{
for (Int32 coordinateIndex = 0; coordinateIndex < result[vectorIndex].Size; coordinateIndex++)
{
result[vectorIndex][coordinateIndex].ShouldBe(this.expectedEigenvectors[matrixIndex][vectorIndex][coordinateIndex], 0.001);
}
}
}
}
public void TestMatrixInverse()
{
IMatrix Ainv = QRAlgorithm.InvertSymmetricMatrix(A);
IMatrix Ipi = A.Multiply(Ainv);
for (int row = 0; row < 2; ++row)
{
Console.WriteLine(Ipi[row]);
}
Assert.Equal(A.Identity(3), Ipi);
Ipi = Ainv.Multiply(A);
Assert.Equal(A.Identity(3), Ipi);
}
/// <summary>
/// реализация QR-декомпозиции
/// </summary>
/// <param name="A - исходная матрица"></param>
/// <param name="Method - метод QR-декомпозиции"></param>
public QRDecomposition(Matrix A, QRAlgorithm Method)
{
R = new Matrix(A.Row, A.Column);
Q = new Matrix(A.Row, A.Column);
//начальная инициализация матрицы ортогональных преобразований
for (int i = 0; i < A.Row; i++)
{
Q.Elem[i][i] = 1.0;
}
switch (Method)
{
case QRAlgorithm.Classic_Gram_Schmidt:
{
GramSchmidt.Classic(A, Q, R);
break;
}
case QRAlgorithm.Modified_Gram_Schmidt:
{
GramSchmidt.Modified(A, Q, R);
break;
}
case QRAlgorithm.Givens:
{
Givens.Orthogon(A, Q, R);
break;
}
case QRAlgorithm.Householder:
{
Householder.Orthogon(A, Q, R);
break;
}
}
}
public void TestQRAlgorithm()
{
IMatrix T, U;
QRAlgorithm.Factorize(A, out T, out U, 20);
}
