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OSVR-Core
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#include <Tridiagonalization.h>
Public Types | |
| enum | { Size = MatrixType::RowsAtCompileTime, SizeMinusOne = Size == Dynamic ? Dynamic : (Size > 1 ? Size - 1 : 1), Options = MatrixType::Options, MaxSize = MatrixType::MaxRowsAtCompileTime, MaxSizeMinusOne = MaxSize == Dynamic ? Dynamic : (MaxSize > 1 ? MaxSize - 1 : 1) } |
| typedef _MatrixType | MatrixType |
Synonym for the template parameter _MatrixType. More... | |
| typedef MatrixType::Scalar | Scalar |
| typedef NumTraits< Scalar >::Real | RealScalar |
| typedef MatrixType::Index | Index |
| typedef Matrix< Scalar, SizeMinusOne, 1, Options &~RowMajor, MaxSizeMinusOne, 1 > | CoeffVectorType |
| typedef internal::plain_col_type< MatrixType, RealScalar >::type | DiagonalType |
| typedef Matrix< RealScalar, SizeMinusOne, 1, Options &~RowMajor, MaxSizeMinusOne, 1 > | SubDiagonalType |
| typedef internal::remove_all< typename MatrixType::RealReturnType >::type | MatrixTypeRealView |
| typedef internal::TridiagonalizationMatrixTReturnType< MatrixTypeRealView > | MatrixTReturnType |
| typedef internal::conditional< NumTraits< Scalar >::IsComplex, typename internal::add_const_on_value_type< typename Diagonal< const MatrixType >::RealReturnType >::type, const Diagonal< const MatrixType > >::type | DiagonalReturnType |
| typedef internal::conditional< NumTraits< Scalar >::IsComplex, typename internal::add_const_on_value_type< typename Diagonal< Block< const MatrixType, SizeMinusOne, SizeMinusOne > >::RealReturnType >::type, const Diagonal< Block< const MatrixType, SizeMinusOne, SizeMinusOne > > >::type | SubDiagonalReturnType |
| typedef HouseholderSequence< MatrixType, typename internal::remove_all< typename CoeffVectorType::ConjugateReturnType >::type > | HouseholderSequenceType |
| Return type of matrixQ() | |
Public Member Functions | |
| Tridiagonalization (Index size=Size==Dynamic ? 2 :Size) | |
| Default constructor. More... | |
| Tridiagonalization (const MatrixType &matrix) | |
| Constructor; computes tridiagonal decomposition of given matrix. More... | |
| Tridiagonalization & | compute (const MatrixType &matrix) |
| Computes tridiagonal decomposition of given matrix. More... | |
| CoeffVectorType | householderCoefficients () const |
| Returns the Householder coefficients. More... | |
| const MatrixType & | packedMatrix () const |
| Returns the internal representation of the decomposition. More... | |
| HouseholderSequenceType | matrixQ () const |
| Returns the unitary matrix Q in the decomposition. More... | |
| MatrixTReturnType | matrixT () const |
| Returns an expression of the tridiagonal matrix T in the decomposition. More... | |
| DiagonalReturnType | diagonal () const |
| Returns the diagonal of the tridiagonal matrix T in the decomposition. More... | |
| SubDiagonalReturnType | subDiagonal () const |
| Returns the subdiagonal of the tridiagonal matrix T in the decomposition. More... | |
Protected Attributes | |
| MatrixType | m_matrix |
| CoeffVectorType | m_hCoeffs |
| bool | m_isInitialized |
Tridiagonal decomposition of a selfadjoint matrix
| _MatrixType | the type of the matrix of which we are computing the tridiagonal decomposition; this is expected to be an instantiation of the Matrix class template. |
This class performs a tridiagonal decomposition of a selfadjoint matrix \( A \) such that: \( A = Q T Q^* \) where \( Q \) is unitary and \( T \) a real symmetric tridiagonal matrix.
A tridiagonal matrix is a matrix which has nonzero elements only on the main diagonal and the first diagonal below and above it. The Hessenberg decomposition of a selfadjoint matrix is in fact a tridiagonal decomposition. This class is used in SelfAdjointEigenSolver to compute the eigenvalues and eigenvectors of a selfadjoint matrix.
Call the function compute() to compute the tridiagonal decomposition of a given matrix. Alternatively, you can use the Tridiagonalization(const MatrixType&) constructor which computes the tridiagonal Schur decomposition at construction time. Once the decomposition is computed, you can use the matrixQ() and matrixT() functions to retrieve the matrices Q and T in the decomposition.
The documentation of Tridiagonalization(const MatrixType&) contains an example of the typical use of this class.
| typedef _MatrixType Eigen::Tridiagonalization< _MatrixType >::MatrixType |
Synonym for the template parameter _MatrixType.
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inline |
Default constructor.
| [in] | size | Positive integer, size of the matrix whose tridiagonal 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.
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Constructor; computes tridiagonal decomposition of given matrix.
| [in] | matrix | Selfadjoint matrix whose tridiagonal decomposition is to be computed. |
This constructor calls compute() to compute the tridiagonal decomposition.
Example:
Output:
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Computes tridiagonal decomposition of given matrix.
| [in] | matrix | Selfadjoint matrix whose tridiagonal decomposition is to be computed. |
*this The tridiagonal decomposition is computed by bringing the columns of the matrix successively in the required form using Householder reflections. The cost is \( 4n^3/3 \) flops, where \( n \) denotes the size of the given matrix.
This method reuses of the allocated data in the Tridiagonalization object, if the size of the matrix does not change.
Example:
Output:
| Tridiagonalization< MatrixType >::DiagonalReturnType Eigen::Tridiagonalization< MatrixType >::diagonal | ( | ) | const |
Returns the diagonal of the tridiagonal matrix T in the decomposition.
Example:
Output:
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Returns the Householder coefficients.
The Householder coefficients allow the reconstruction of the matrix \( Q \) in the tridiagonal decomposition from the packed data.
Example:
Output:
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Returns the unitary matrix Q in the decomposition.
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.
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Returns an expression of the tridiagonal matrix T in the decomposition.
Currently, this function can be used to extract the matrix T from internal data and copy it to a dense matrix object. In most cases, it may be sufficient to directly use the packed matrix or the vector expressions returned by diagonal() and subDiagonal() instead of creating a new dense copy matrix with this function.
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Returns the internal representation of the decomposition.
The returned matrix contains the following information:
See LAPACK for further details on this packed storage.
Example:
Output:
| Tridiagonalization< MatrixType >::SubDiagonalReturnType Eigen::Tridiagonalization< MatrixType >::subDiagonal | ( | ) | const |
Returns the subdiagonal of the tridiagonal matrix T in the decomposition.
1.8.12