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clean old stuff used to support precompilation inside a binary lib

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This commit is contained in:
Gael Guennebaud
2010-06-07 14:47:20 +02:00
parent bfeba41174
commit 7726cc8a29
11 changed files with 76 additions and 206 deletions
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74
Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
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@@ -43,7 +43,7 @@
* A matrix \f$ A \f$ is selfadjoint if it equals its adjoint. For real
* matrices, this means that the matrix is symmetric: it equals its
* transpose. This class computes the eigenvalues and eigenvectors of a
* selfadjoint matrix. These are the scalars \f$ \lambda \f$ and vectors
* selfadjoint matrix. These are the scalars \f$ \lambda \f$ and vectors
* \f$ v \f$ such that \f$ Av = \lambda v \f$. The eigenvalues of a
* selfadjoint matrix are always real. If \f$ D \f$ is a diagonal matrix with
* the eigenvalues on the diagonal, and \f$ V \f$ is a matrix with the
@@ -68,7 +68,7 @@
*
* The documentation for SelfAdjointEigenSolver(const MatrixType&, bool)
* contains an example of the typical use of this class.
*
*
* \sa MatrixBase::eigenvalues(), class EigenSolver, class ComplexEigenSolver
*/
template<typename _MatrixType> class SelfAdjointEigenSolver
@@ -87,15 +87,15 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::Index Index;
/** \brief Real scalar type for \p _MatrixType.
/** \brief Real scalar type for \p _MatrixType.
*
* This is just \c Scalar if #Scalar is real (e.g., \c float or
* This is just \c Scalar if #Scalar is real (e.g., \c float or
* \c double), and the type of the real part of \c Scalar if #Scalar is
* complex.
*/
typedef typename NumTraits<Scalar>::Real RealScalar;
/** \brief Type for vector of eigenvalues as returned by eigenvalues().
/** \brief Type for vector of eigenvalues as returned by eigenvalues().
*
* This is a column vector with entries of type #RealScalar.
* The length of the vector is the size of \p _MatrixType.
@@ -130,7 +130,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
* This constructor is useful for dynamic-size matrices, when the user
* intends to perform decompositions via compute(const MatrixType&, bool)
* or compute(const MatrixType&, const MatrixType&, bool). The \p size
* parameter is only used as a hint. It is not an error to give a wrong
* parameter is only used as a hint. It is not an error to give a wrong
* \p size, but it may impair performance.
*
* \sa compute(const MatrixType&, bool) for an example
@@ -143,13 +143,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
m_isInitialized(false)
{}
/** \brief Constructor; computes eigendecomposition of given matrix.
*
/** \brief Constructor; computes eigendecomposition of given matrix.
*
* \param[in] matrix Selfadjoint matrix whose eigendecomposition is to
* be computed.
* be computed.
* \param[in] computeEigenvectors If true, both the eigenvectors and the
* eigenvalues are computed; if false, only the eigenvalues are
* computed.
* computed.
*
* This constructor calls compute(const MatrixType&, bool) to compute the
* eigenvalues of the matrix \p matrix. The eigenvectors are computed if
@@ -158,7 +158,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
* Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.cpp
* Output: \verbinclude SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.out
*
* \sa compute(const MatrixType&, bool),
* \sa compute(const MatrixType&, bool),
* SelfAdjointEigenSolver(const MatrixType&, const MatrixType&, bool)
*/
SelfAdjointEigenSolver(const MatrixType& matrix, bool computeEigenvectors = true)
@@ -172,14 +172,14 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
}
/** \brief Constructor; computes eigendecomposition of given matrix pencil.
*
*
* \param[in] matA Selfadjoint matrix in matrix pencil.
* \param[in] matB Positive-definite matrix in matrix pencil.
* \param[in] computeEigenvectors If true, both the eigenvectors and the
* eigenvalues are computed; if false, only the eigenvalues are
* computed.
* computed.
*
* This constructor calls compute(const MatrixType&, const MatrixType&, bool)
* This constructor calls compute(const MatrixType&, const MatrixType&, bool)
* to compute the eigenvalues and (if requested) the eigenvectors of the
* generalized eigenproblem \f$ Ax = \lambda B x \f$ with \a matA the
* selfadjoint matrix \f$ A \f$ and \a matB the positive definite matrix
@@ -189,7 +189,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
* Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType2.cpp
* Output: \verbinclude SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType2.out
*
* \sa compute(const MatrixType&, const MatrixType&, bool),
* \sa compute(const MatrixType&, const MatrixType&, bool),
* SelfAdjointEigenSolver(const MatrixType&, bool)
*/
SelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = true)
@@ -202,13 +202,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
compute(matA, matB, computeEigenvectors);
}
/** \brief Computes eigendecomposition of given matrix.
*
/** \brief Computes eigendecomposition of given matrix.
*
* \param[in] matrix Selfadjoint matrix whose eigendecomposition is to
* be computed.
* be computed.
* \param[in] computeEigenvectors If true, both the eigenvectors and the
* eigenvalues are computed; if false, only the eigenvalues are
* computed.
* computed.
* \returns Reference to \c *this
*
* This function computes the eigenvalues of \p matrix. The eigenvalues()
@@ -236,13 +236,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
*/
SelfAdjointEigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
/** \brief Computes eigendecomposition of given matrix pencil.
*
/** \brief Computes eigendecomposition of given matrix pencil.
*
* \param[in] matA Selfadjoint matrix in matrix pencil.
* \param[in] matB Positive-definite matrix in matrix pencil.
* \param[in] computeEigenvectors If true, both the eigenvectors and the
* eigenvalues are computed; if false, only the eigenvalues are
* computed.
* computed.
* \returns Reference to \c *this
*
* This function computes eigenvalues and (if requested) the eigenvectors
@@ -253,11 +253,11 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
* eigenvectors are also computed and can be retrieved by calling
* eigenvectors().
*
* The implementation uses LLT to compute the Cholesky decomposition
* The implementation uses LLT to compute the Cholesky decomposition
* \f$ B = LL^* \f$ and calls compute(const MatrixType&, bool) to compute
* the eigendecomposition \f$ L^{-1} A (L^*)^{-1} \f$. This solves the
* generalized eigenproblem, because any solution of the generalized
* eigenproblem \f$ Ax = \lambda B x \f$ corresponds to a solution
* eigenproblem \f$ Ax = \lambda B x \f$ corresponds to a solution
* \f$ L^{-1} A (L^*)^{-1} (L^* x) = \lambda (L^* x) \f$ of the
* eigenproblem for \f$ L^{-1} A (L^*)^{-1} \f$.
*
@@ -268,7 +268,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
*/
SelfAdjointEigenSolver& compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = true);
/** \brief Returns the eigenvectors of given matrix (pencil).
/** \brief Returns the eigenvectors of given matrix (pencil).
*
* \returns A const reference to the matrix whose columns are the eigenvectors.
*
@@ -293,7 +293,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
return m_eivec;
}
/** \brief Returns the eigenvalues of given matrix (pencil).
/** \brief Returns the eigenvalues of given matrix (pencil).
*
* \returns A const reference to the column vector containing the eigenvalues.
*
@@ -307,13 +307,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
*
* \sa eigenvectors(), MatrixBase::eigenvalues()
*/
const RealVectorType& eigenvalues() const
{
const RealVectorType& eigenvalues() const
{
ei_assert(m_isInitialized && "SelfAdjointEigenSolver is not initialized.");
return m_eivalues;
return m_eivalues;
}
/** \brief Computes the positive-definite square root of the matrix.
/** \brief Computes the positive-definite square root of the matrix.
*
* \returns the positive-definite square root of the matrix
*
@@ -328,7 +328,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
* Example: \include SelfAdjointEigenSolver_operatorSqrt.cpp
* Output: \verbinclude SelfAdjointEigenSolver_operatorSqrt.out
*
* \sa operatorInverseSqrt(),
* \sa operatorInverseSqrt(),
* \ref MatrixFunctions_Module "MatrixFunctions Module"
*/
MatrixType operatorSqrt() const
@@ -338,7 +338,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
return m_eivec * m_eivalues.cwiseSqrt().asDiagonal() * m_eivec.adjoint();
}
/** \brief Computes the inverse square root of the matrix.
/** \brief Computes the inverse square root of the matrix.
*
* \returns the inverse positive-definite square root of the matrix
*
@@ -375,7 +375,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
/** \brief Maximum number of iterations.
*
* Maximum number of iterations allowed for an eigenvalue to converge.
* Maximum number of iterations allowed for an eigenvalue to converge.
*/
static const int m_maxIterations = 30;
@@ -389,8 +389,6 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
bool m_eigenvectorsOk;
};
#ifndef EIGEN_HIDE_HEAVY_CODE
/** \internal
*
* \eigenvalues_module \ingroup Eigenvalues_Module
@@ -467,7 +465,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>::compute(
ei_tridiagonal_qr_step(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n);
}
if (iter <= m_maxIterations)
if (iter <= m_maxIterations)
m_info = Success;
else
m_info = NoConvergence;
@@ -531,9 +529,6 @@ compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors
return *this;
}
#endif // EIGEN_HIDE_HEAVY_CODE
#ifndef EIGEN_EXTERN_INSTANTIATIONS
template<typename RealScalar, typename Scalar, typename Index>
static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
{
@@ -575,6 +570,5 @@ static void ei_tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index
}
}
}
#endif
#endif // EIGEN_SELFADJOINTEIGENSOLVER_H