Type for vector of Householder coefficients.

This is column vector with entries of type Scalar. The length of the vector is one less than the size of MatrixType, if it is a fixed-side type.

Deprecated:

since Eigen 3.3

Default constructor; the decomposition will be computed later.

Parameters

[in]

size

The size of the matrix whose Hessenberg decomposition will be computed.

The default constructor is useful in cases in which the user intends to perform decompositions via compute(). The size parameter is only used as a hint. It is not an error to give a wrong size, but it may impair performance.

See also

compute() for an example.

Constructor; computes Hessenberg decomposition of given matrix.

Parameters

[in]

matrix

Square matrix whose Hessenberg decomposition is to be computed.

This constructor calls compute() to compute the Hessenberg decomposition.

See also

matrixH() for an example.

Computes Hessenberg decomposition of given matrix.

Parameters

[in]

matrix

Square matrix whose Hessenberg decomposition is to be computed.

Returns

Reference to *this

The Hessenberg decomposition is computed by bringing the columns of the matrix successively in the required form using Householder reflections (see, e.g., Algorithm 7.4.2 in Golub & Van Loan, Matrix Computations). The cost is \( 10n^3/3 \) flops, where \( n \) denotes the size of the given matrix.

This method reuses of the allocated data in the HessenbergDecomposition object.

Example:

MatrixXcf A = MatrixXcf::Random(4,4);
HessenbergDecomposition<MatrixXcf> hd(4);
hd.compute(A);
cout << "The matrix H in the decomposition of A is:" << endl << hd.matrixH() << endl;
hd.compute(2*A); // re-use hd to compute and store decomposition of 2A
cout << "The matrix H in the decomposition of 2A is:" << endl << hd.matrixH() << endl;

Output:

The matrix H in the decomposition of A is:
    (-0.211,0.68)     (0.346,0.216)  (-0.688,0.00979)    (0.0451,0.584)
        (-1.45,0) (-0.0574,-0.0123)    (-0.196,0.385)     (0.395,0.389)
            (0,0)          (1.68,0)   (-0.397,-0.552)    (0.156,-0.241)
            (0,0)             (0,0)          (1.56,0)    (0.876,-0.423)
The matrix H in the decomposition of 2A is:
   (-0.422,1.36)    (0.691,0.431)   (-1.38,0.0196)    (0.0902,1.17)
       (-2.91,0) (-0.115,-0.0246)    (-0.392,0.77)    (0.791,0.777)
           (0,0)         (3.36,0)    (-0.795,-1.1)   (0.311,-0.482)
           (0,0)            (0,0)         (3.12,0)    (1.75,-0.846)

Returns the Householder coefficients.

Returns

a const reference to the vector of Householder coefficients

Precondition

Either the constructor HessenbergDecomposition(const MatrixType&) or the member function compute(const MatrixType&) has been called before to compute the Hessenberg decomposition of a matrix.

The Householder coefficients allow the reconstruction of the matrix \( Q \) in the Hessenberg decomposition from the packed data.

See also

packedMatrix(), Householder module

Constructs the Hessenberg matrix H in the decomposition.

Returns

expression object representing the matrix H

Precondition

Either the constructor HessenbergDecomposition(const MatrixType&) or the member function compute(const MatrixType&) has been called before to compute the Hessenberg decomposition of a matrix.

The object returned by this function constructs the Hessenberg matrix H when it is assigned to a matrix or otherwise evaluated. The matrix H is constructed from the packed matrix as returned by packedMatrix(): The upper part (including the subdiagonal) of the packed matrix contains the matrix H. It may sometimes be better to directly use the packed matrix instead of constructing the matrix H.

Example:

Matrix4f A = MatrixXf::Random(4,4);
cout << "Here is a random 4x4 matrix:" << endl << A << endl;
HessenbergDecomposition<MatrixXf> hessOfA(A);
MatrixXf H = hessOfA.matrixH();
cout << "The Hessenberg matrix H is:" << endl << H << endl;
MatrixXf Q = hessOfA.matrixQ();
cout << "The orthogonal matrix Q is:" << endl << Q << endl;
cout << "Q H Q^T is:" << endl << Q * H * Q.transpose() << endl;

Output:

Here is a random 4x4 matrix:
   0.68   0.823  -0.444   -0.27
 -0.211  -0.605   0.108  0.0268
  0.566   -0.33 -0.0452   0.904
  0.597   0.536   0.258   0.832
The Hessenberg matrix H is:
   0.68  -0.691  -0.645   0.235
  0.849   0.836  -0.419   0.794
      0  -0.469  -0.547 -0.0731
      0       0  -0.559  -0.107
The orthogonal matrix Q is:
      1       0       0       0
      0  -0.249  -0.958   0.144
      0   0.667  -0.277  -0.692
      0   0.703 -0.0761   0.707
Q H Q^T is:
   0.68   0.823  -0.444   -0.27
 -0.211  -0.605   0.108  0.0268
  0.566   -0.33 -0.0452   0.904
  0.597   0.536   0.258   0.832

See also

matrixQ(), packedMatrix()

Reconstructs the orthogonal matrix Q in the decomposition.

Returns

object representing the matrix Q

Precondition

Either the constructor HessenbergDecomposition(const MatrixType&) or the member function compute(const MatrixType&) has been called before to compute the Hessenberg decomposition of a matrix.

This function returns a light-weight object of template class HouseholderSequence. You can either apply it directly to a matrix or you can convert it to a matrix of type MatrixType.

See also

matrixH() for an example, class HouseholderSequence

Returns the internal representation of the decomposition.

Returns

a const reference to a matrix with the internal representation of the decomposition.

Precondition

Either the constructor HessenbergDecomposition(const MatrixType&) or the member function compute(const MatrixType&) has been called before to compute the Hessenberg decomposition of a matrix.

The returned matrix contains the following information:

• the upper part and lower sub-diagonal represent the Hessenberg matrix H
• the rest of the lower part contains the Householder vectors that, combined with Householder coefficients returned by householderCoefficients(), allows to reconstruct the matrix Q as \( Q = H_{N-1} \ldots H_1 H_0 \). Here, the matrices \( H_i \) are the Householder transformations \( H_i = (I - h_i v_i v_i^T) \) where \( h_i \) is the \( i \)th Householder coefficient and \( v_i \) is the Householder vector defined by \( v_i = [ 0, \ldots, 0, 1, M(i+2,i), \ldots, M(N-1,i) ]^T \) with M the matrix returned by this function.

See LAPACK for further details on this packed storage.

Example:

Matrix4d A = Matrix4d::Random(4,4);
cout << "Here is a random 4x4 matrix:" << endl << A << endl;
HessenbergDecomposition<Matrix4d> hessOfA(A);
Matrix4d pm = hessOfA.packedMatrix();
cout << "The packed matrix M is:" << endl << pm << endl;
cout << "The upper Hessenberg part corresponds to the matrix H, which is:" 
     << endl << hessOfA.matrixH() << endl;
Vector3d hc = hessOfA.householderCoefficients();
cout << "The vector of Householder coefficients is:" << endl << hc << endl;

Output:

Here is a random 4x4 matrix:
   0.68   0.823  -0.444   -0.27
 -0.211  -0.605   0.108  0.0268
  0.566   -0.33 -0.0452   0.904
  0.597   0.536   0.258   0.832
The packed matrix M is:
   0.68  -0.691  -0.645   0.235
  0.849   0.836  -0.419   0.794
 -0.534  -0.469  -0.547 -0.0731
 -0.563   0.344  -0.559  -0.107
The upper Hessenberg part corresponds to the matrix H, which is:
   0.68  -0.691  -0.645   0.235
  0.849   0.836  -0.419   0.794
      0  -0.469  -0.547 -0.0731
      0       0  -0.559  -0.107
The vector of Householder coefficients is:
1.25
1.79
   0

See also

householderCoefficients()