/// <summary>
/// Initializes a new instance of the <see cref="UserEvd"/> class. This object will compute the
/// the eigenvalue decomposition when the constructor is called and cache it's decomposition.
/// </summary>
/// <param name="matrix">The matrix to factor.</param>
/// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
/// <exception cref="ArgumentException">If EVD algorithm failed to converge with matrix <paramref name="matrix"/>.</exception>
public UserEvd(Matrix <Complex32> matrix)
{
if (matrix == null)
{
throw new ArgumentNullException("matrix");
}
if (matrix.RowCount != matrix.ColumnCount)
{
throw new ArgumentException(Resources.ArgumentMatrixSquare);
}
var order = matrix.RowCount;
// Initialize matricies for eigenvalues and eigenvectors
MatrixEv = DenseMatrix.Identity(order);
MatrixD = matrix.CreateMatrix(order, order);
VectorEv = new LinearAlgebra.Complex.DenseVector(order);
IsSymmetric = true;
for (var i = 0; IsSymmetric && i < order; i++)
{
for (var j = 0; IsSymmetric && j < order; j++)
{
IsSymmetric &= matrix.At(i, j) == matrix.At(j, i).Conjugate();
}
}
if (IsSymmetric)
{
var matrixCopy = matrix.ToArray();
var tau = new Complex32[order];
var d = new float[order];
var e = new float[order];
SymmetricTridiagonalize(matrixCopy, d, e, tau, order);
SymmetricDiagonalize(d, e, order);
SymmetricUntridiagonalize(matrixCopy, tau, order);
for (var i = 0; i < order; i++)
{
VectorEv[i] = new Complex(d[i], e[i]);
}
}
else
{
var matrixH = matrix.ToArray();
NonsymmetricReduceToHessenberg(matrixH, order);
NonsymmetricReduceHessenberToRealSchur(matrixH, order);
}
for (var i = 0; i < VectorEv.Count; i++)
{
MatrixD.At(i, i, (Complex32)VectorEv[i]);
}
}
/// <summary>
/// Initializes a new instance of the <see cref="UserEvd"/> class. This object will compute the
/// the eigenvalue decomposition when the constructor is called and cache it's decomposition.
/// </summary>
/// <param name="matrix">The matrix to factor.</param>
/// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
/// <exception cref="ArgumentException">If EVD algorithm failed to converge with matrix <paramref name="matrix"/>.</exception>
public UserEvd(Matrix<Complex32> matrix)
{
if (matrix == null)
{
throw new ArgumentNullException("matrix");
}
if (matrix.RowCount != matrix.ColumnCount)
{
throw new ArgumentException(Resources.ArgumentMatrixSquare);
}
var order = matrix.RowCount;
// Initialize matricies for eigenvalues and eigenvectors
MatrixEv = DenseMatrix.Identity(order);
MatrixD = matrix.CreateMatrix(order, order);
VectorEv = new LinearAlgebra.Complex.DenseVector(order);
IsSymmetric = true;
for (var i = 0; IsSymmetric && i < order; i++)
{
for (var j = 0; IsSymmetric && j < order; j++)
{
IsSymmetric &= matrix.At(i, j) == matrix.At(j, i).Conjugate();
}
}
if (IsSymmetric)
{
var matrixCopy = matrix.ToArray();
var tau = new Complex32[order];
var d = new float[order];
var e = new float[order];
SymmetricTridiagonalize(matrixCopy, d, e, tau, order);
SymmetricDiagonalize(d, e, order);
SymmetricUntridiagonalize(matrixCopy, tau, order);
for (var i = 0; i < order; i++)
{
VectorEv[i] = new Complex(d[i], e[i]);
}
}
else
{
var matrixH = matrix.ToArray();
NonsymmetricReduceToHessenberg(matrixH, order);
NonsymmetricReduceHessenberToRealSchur(matrixH, order);
}
for (var i = 0; i < VectorEv.Count; i++)
{
MatrixD.At(i, i, (Complex32)VectorEv[i]);
}
}
/// <summary>
/// Initializes a new instance of the <see cref="UserEvd"/> class. This object will compute the
/// the eigenvalue decomposition when the constructor is called and cache it's decomposition.
/// </summary>
/// <param name="matrix">The matrix to factor.</param>
/// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
/// <exception cref="ArgumentException">If EVD algorithm failed to converge with matrix <paramref name="matrix"/>.</exception>
public UserEvd(Matrix<float> matrix)
{
if (matrix == null)
{
throw new ArgumentNullException("matrix");
}
if (matrix.RowCount != matrix.ColumnCount)
{
throw new ArgumentException(Resources.ArgumentMatrixSquare);
}
var order = matrix.RowCount;
// Initialize matricies for eigenvalues and eigenvectors
MatrixEv = matrix.CreateMatrix(order, order);
MatrixD = matrix.CreateMatrix(order, order);
VectorEv = new LinearAlgebra.Complex.DenseVector(order);
IsSymmetric = true;
for (var i = 0; IsSymmetric && i < order; i++)
{
for (var j = 0; IsSymmetric && j < order; j++)
{
IsSymmetric &= matrix.At(i, j) == matrix.At(j, i);
}
}
var d = new float[order];
var e = new float[order];
if (IsSymmetric)
{
matrix.CopyTo(MatrixEv);
d = MatrixEv.Row(order - 1).ToArray();
SymmetricTridiagonalize(d, e, order);
SymmetricDiagonalize(d, e, order);
}
else
{
var matrixH = matrix.ToArray();
NonsymmetricReduceToHessenberg(matrixH, order);
NonsymmetricReduceHessenberToRealSchur(matrixH, d, e, order);
}
for (var i = 0; i < order; i++)
{
MatrixD.At(i, i, d[i]);
if (e[i] > 0)
{
MatrixD.At(i, i + 1, e[i]);
}
else if (e[i] < 0)
{
MatrixD.At(i, i - 1, e[i]);
}
}
for (var i = 0; i < order; i++)
{
VectorEv[i] = new Complex(d[i], e[i]);
}
}
/// <summary>
/// Initializes a new instance of the <see cref="UserEvd"/> class. This object will compute the
/// the eigenvalue decomposition when the constructor is called and cache it's decomposition.
/// </summary>
/// <param name="matrix">The matrix to factor.</param>
/// <exception cref="ArgumentNullException">If <paramref name="matrix"/> is <c>null</c>.</exception>
/// <exception cref="ArgumentException">If EVD algorithm failed to converge with matrix <paramref name="matrix"/>.</exception>
public UserEvd(Matrix <float> matrix)
{
if (matrix == null)
{
throw new ArgumentNullException("matrix");
}
if (matrix.RowCount != matrix.ColumnCount)
{
throw new ArgumentException(Resources.ArgumentMatrixSquare);
}
var order = matrix.RowCount;
// Initialize matricies for eigenvalues and eigenvectors
MatrixEv = matrix.CreateMatrix(order, order);
MatrixD = matrix.CreateMatrix(order, order);
VectorEv = new LinearAlgebra.Complex.DenseVector(order);
IsSymmetric = true;
for (var i = 0; IsSymmetric && i < order; i++)
{
for (var j = 0; IsSymmetric && j < order; j++)
{
IsSymmetric &= matrix.At(i, j) == matrix.At(j, i);
}
}
var d = new float[order];
var e = new float[order];
if (IsSymmetric)
{
matrix.CopyTo(MatrixEv);
d = MatrixEv.Row(order - 1).ToArray();
SymmetricTridiagonalize(d, e, order);
SymmetricDiagonalize(d, e, order);
}
else
{
var matrixH = matrix.ToArray();
NonsymmetricReduceToHessenberg(matrixH, order);
NonsymmetricReduceHessenberToRealSchur(matrixH, d, e, order);
}
for (var i = 0; i < order; i++)
{
MatrixD.At(i, i, d[i]);
if (e[i] > 0)
{
MatrixD.At(i, i + 1, e[i]);
}
else if (e[i] < 0)
{
MatrixD.At(i, i - 1, e[i]);
}
}
for (var i = 0; i < order; i++)
{
VectorEv[i] = new Complex(d[i], e[i]);
}
}
