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ADD: added other eigen lib

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This commit is contained in:
Henry Winkel
2022-12-21 16:19:04 +01:00
parent a570766dc6
commit 9e56c7f2c0
832 changed files with 36586 additions and 20006 deletions
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21
libs/eigen/Eigen/src/Eigenvalues/ComplexEigenSolver.h
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@@ -14,6 +14,8 @@
#include "./ComplexSchur.h"
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \eigenvalues_module \ingroup Eigenvalues_Module
@@ -23,7 +25,7 @@ namespace Eigen {
*
* \brief Computes eigenvalues and eigenvectors of general complex matrices
*
* \tparam _MatrixType the type of the matrix of which we are
* \tparam MatrixType_ the type of the matrix of which we are
* computing the eigendecomposition; this is expected to be an
* instantiation of the Matrix class template.
*
@@ -42,12 +44,12 @@ namespace Eigen {
*
* \sa class EigenSolver, class SelfAdjointEigenSolver
*/
template<typename _MatrixType> class ComplexEigenSolver
template<typename MatrixType_> class ComplexEigenSolver
{
public:
/** \brief Synonym for the template parameter \p _MatrixType. */
typedef _MatrixType MatrixType;
/** \brief Synonym for the template parameter \p MatrixType_. */
typedef MatrixType_ MatrixType;
enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
@@ -236,12 +238,9 @@ template<typename _MatrixType> class ComplexEigenSolver
}
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
EigenvectorType m_eivec;
EigenvalueType m_eivalues;
ComplexSchur<MatrixType> m_schur;
@@ -260,8 +259,6 @@ template<typename InputType>
ComplexEigenSolver<MatrixType>&
ComplexEigenSolver<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeEigenvectors)
{
check_template_parameters();
// this code is inspired from Jampack
eigen_assert(matrix.cols() == matrix.rows());

18
libs/eigen/Eigen/src/Eigenvalues/ComplexSchur.h
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@@ -14,6 +14,8 @@
#include "./HessenbergDecomposition.h"
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
@@ -27,7 +29,7 @@ template<typename MatrixType, bool IsComplex> struct complex_schur_reduce_to_hes
*
* \brief Performs a complex Schur decomposition of a real or complex square matrix
*
* \tparam _MatrixType the type of the matrix of which we are
* \tparam MatrixType_ the type of the matrix of which we are
* computing the Schur decomposition; this is expected to be an
* instantiation of the Matrix class template.
*
@@ -48,10 +50,10 @@ template<typename MatrixType, bool IsComplex> struct complex_schur_reduce_to_hes
*
* \sa class RealSchur, class EigenSolver, class ComplexEigenSolver
*/
template<typename _MatrixType> class ComplexSchur
template<typename MatrixType_> class ComplexSchur
{
public:
typedef _MatrixType MatrixType;
typedef MatrixType_ MatrixType;
enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
@@ -60,12 +62,12 @@ template<typename _MatrixType> class ComplexSchur
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
};
/** \brief Scalar type for matrices of type \p _MatrixType. */
/** \brief Scalar type for matrices of type \p MatrixType_. */
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
/** \brief Complex scalar type for \p _MatrixType.
/** \brief Complex scalar type for \p MatrixType_.
*
* This is \c std::complex<Scalar> if #Scalar is real (e.g.,
* \c float or \c double) and just \c Scalar if #Scalar is
@@ -76,7 +78,7 @@ template<typename _MatrixType> class ComplexSchur
/** \brief Type for the matrices in the Schur decomposition.
*
* This is a square matrix with entries of type #ComplexScalar.
* The size is the same as the size of \p _MatrixType.
* The size is the same as the size of \p MatrixType_.
*/
typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, MaxColsAtCompileTime> ComplexMatrixType;
@@ -259,7 +261,7 @@ template<typename _MatrixType> class ComplexSchur
friend struct internal::complex_schur_reduce_to_hessenberg<MatrixType, NumTraits<Scalar>::IsComplex>;
};
/** If m_matT(i+1,i) is neglegible in floating point arithmetic
/** If m_matT(i+1,i) is negligible in floating point arithmetic
* compared to m_matT(i,i) and m_matT(j,j), then set it to zero and
* return true, else return false. */
template<typename MatrixType>
@@ -306,7 +308,7 @@ typename ComplexSchur<MatrixType>::ComplexScalar ComplexSchur<MatrixType>::compu
// In this case, det==0, and all we have to do is checking that eival2_norm!=0
if(eival1_norm > eival2_norm)
eival2 = det / eival1;
else if(eival2_norm!=RealScalar(0))
else if(!numext::is_exactly_zero(eival2_norm))
eival1 = det / eival2;
// choose the eigenvalue closest to the bottom entry of the diagonal

2
libs/eigen/Eigen/src/Eigenvalues/ComplexSchur_LAPACKE.h
View File

@@ -33,6 +33,8 @@
#ifndef EIGEN_COMPLEX_SCHUR_LAPACKE_H
#define EIGEN_COMPLEX_SCHUR_LAPACKE_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \internal Specialization for the data types supported by LAPACKe */

10
libs/eigen/Eigen/src/Eigenvalues/EigenSolver.h
View File

@@ -13,6 +13,8 @@
#include "./RealSchur.h"
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \eigenvalues_module \ingroup Eigenvalues_Module
@@ -22,7 +24,7 @@ namespace Eigen {
*
* \brief Computes eigenvalues and eigenvectors of general matrices
*
* \tparam _MatrixType the type of the matrix of which we are computing the
* \tparam MatrixType_ the type of the matrix of which we are computing the
* eigendecomposition; this is expected to be an instantiation of the Matrix
* class template. Currently, only real matrices are supported.
*
@@ -61,12 +63,12 @@ namespace Eigen {
*
* \sa MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver
*/
template<typename _MatrixType> class EigenSolver
template<typename MatrixType_> class EigenSolver
{
public:
/** \brief Synonym for the template parameter \p _MatrixType. */
typedef _MatrixType MatrixType;
/** \brief Synonym for the template parameter \p MatrixType_. */
typedef MatrixType_ MatrixType;
enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,

60
libs/eigen/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h
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@@ -14,6 +14,8 @@
#include "./RealQZ.h"
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \eigenvalues_module \ingroup Eigenvalues_Module
@@ -23,7 +25,7 @@ namespace Eigen {
*
* \brief Computes the generalized eigenvalues and eigenvectors of a pair of general matrices
*
* \tparam _MatrixType the type of the matrices of which we are computing the
* \tparam MatrixType_ the type of the matrices of which we are computing the
* eigen-decomposition; this is expected to be an instantiation of the Matrix
* class template. Currently, only real matrices are supported.
*
@@ -55,12 +57,12 @@ namespace Eigen {
*
* \sa MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver
*/
template<typename _MatrixType> class GeneralizedEigenSolver
template<typename MatrixType_> class GeneralizedEigenSolver
{
public:
/** \brief Synonym for the template parameter \p _MatrixType. */
typedef _MatrixType MatrixType;
/** \brief Synonym for the template parameter \p MatrixType_. */
typedef MatrixType_ MatrixType;
enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
@@ -119,8 +121,8 @@ template<typename _MatrixType> class GeneralizedEigenSolver
: m_eivec(),
m_alphas(),
m_betas(),
m_valuesOkay(false),
m_vectorsOkay(false),
m_computeEigenvectors(false),
m_isInitialized(false),
m_realQZ()
{}
@@ -134,8 +136,8 @@ template<typename _MatrixType> class GeneralizedEigenSolver
: m_eivec(size, size),
m_alphas(size),
m_betas(size),
m_valuesOkay(false),
m_vectorsOkay(false),
m_computeEigenvectors(false),
m_isInitialized(false),
m_realQZ(size),
m_tmp(size)
{}
@@ -156,8 +158,8 @@ template<typename _MatrixType> class GeneralizedEigenSolver
: m_eivec(A.rows(), A.cols()),
m_alphas(A.cols()),
m_betas(A.cols()),
m_valuesOkay(false),
m_vectorsOkay(false),
m_computeEigenvectors(false),
m_isInitialized(false),
m_realQZ(A.cols()),
m_tmp(A.cols())
{
@@ -177,7 +179,8 @@ template<typename _MatrixType> class GeneralizedEigenSolver
* \sa eigenvalues()
*/
EigenvectorsType eigenvectors() const {
eigen_assert(m_vectorsOkay && "Eigenvectors for GeneralizedEigenSolver were not calculated.");
eigen_assert(info() == Success && "GeneralizedEigenSolver failed to compute eigenvectors");
eigen_assert(m_computeEigenvectors && "Eigenvectors for GeneralizedEigenSolver were not calculated");
return m_eivec;
}
@@ -201,7 +204,7 @@ template<typename _MatrixType> class GeneralizedEigenSolver
*/
EigenvalueType eigenvalues() const
{
eigen_assert(m_valuesOkay && "GeneralizedEigenSolver is not initialized.");
eigen_assert(info() == Success && "GeneralizedEigenSolver failed to compute eigenvalues.");
return EigenvalueType(m_alphas,m_betas);
}
@@ -210,9 +213,9 @@ template<typename _MatrixType> class GeneralizedEigenSolver
* This vector permits to reconstruct the j-th eigenvalues as alphas(i)/betas(j).
*
* \sa betas(), eigenvalues() */
ComplexVectorType alphas() const
const ComplexVectorType& alphas() const
{
eigen_assert(m_valuesOkay && "GeneralizedEigenSolver is not initialized.");
eigen_assert(info() == Success && "GeneralizedEigenSolver failed to compute alphas.");
return m_alphas;
}
@@ -221,9 +224,9 @@ template<typename _MatrixType> class GeneralizedEigenSolver
* This vector permits to reconstruct the j-th eigenvalues as alphas(i)/betas(j).
*
* \sa alphas(), eigenvalues() */
VectorType betas() const
const VectorType& betas() const
{
eigen_assert(m_valuesOkay && "GeneralizedEigenSolver is not initialized.");
eigen_assert(info() == Success && "GeneralizedEigenSolver failed to compute betas.");
return m_betas;
}
@@ -254,7 +257,7 @@ template<typename _MatrixType> class GeneralizedEigenSolver
ComputationInfo info() const
{
eigen_assert(m_valuesOkay && "EigenSolver is not initialized.");
eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
return m_realQZ.info();
}
@@ -267,17 +270,15 @@ template<typename _MatrixType> class GeneralizedEigenSolver
}
protected:
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL);
}
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
EIGEN_STATIC_ASSERT(!NumTraits<Scalar>::IsComplex, NUMERIC_TYPE_MUST_BE_REAL)
EigenvectorsType m_eivec;
ComplexVectorType m_alphas;
VectorType m_betas;
bool m_valuesOkay, m_vectorsOkay;
bool m_computeEigenvectors;
bool m_isInitialized;
RealQZ<MatrixType> m_realQZ;
ComplexVectorType m_tmp;
};
@@ -286,14 +287,10 @@ template<typename MatrixType>
GeneralizedEigenSolver<MatrixType>&
GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors)
{
check_template_parameters();
using std::sqrt;
using std::abs;
eigen_assert(A.cols() == A.rows() && B.cols() == A.rows() && B.cols() == B.rows());
Index size = A.cols();
m_valuesOkay = false;
m_vectorsOkay = false;
// Reduce to generalized real Schur form:
// A = Q S Z and B = Q T Z
m_realQZ.compute(A, B, computeEigenvectors);
@@ -406,10 +403,9 @@ GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixTyp
i += 2;
}
}
m_valuesOkay = true;
m_vectorsOkay = computeEigenvectors;
}
m_computeEigenvectors = computeEigenvectors;
m_isInitialized = true;
return *this;
}

14
libs/eigen/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h
View File

@@ -13,6 +13,8 @@
#include "./Tridiagonalization.h"
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \eigenvalues_module \ingroup Eigenvalues_Module
@@ -22,7 +24,7 @@ namespace Eigen {
*
* \brief Computes eigenvalues and eigenvectors of the generalized selfadjoint eigen problem
*
* \tparam _MatrixType the type of the matrix of which we are computing the
* \tparam MatrixType_ the type of the matrix of which we are computing the
* eigendecomposition; this is expected to be an instantiation of the Matrix
* class template.
*
@@ -44,19 +46,19 @@ namespace Eigen {
*
* \sa class SelfAdjointEigenSolver, class EigenSolver, class ComplexEigenSolver
*/
template<typename _MatrixType>
class GeneralizedSelfAdjointEigenSolver : public SelfAdjointEigenSolver<_MatrixType>
template<typename MatrixType_>
class GeneralizedSelfAdjointEigenSolver : public SelfAdjointEigenSolver<MatrixType_>
{
typedef SelfAdjointEigenSolver<_MatrixType> Base;
typedef SelfAdjointEigenSolver<MatrixType_> Base;
public:
typedef _MatrixType MatrixType;
typedef MatrixType_ MatrixType;
/** \brief Default constructor for fixed-size matrices.
*
* The default constructor is useful in cases in which the user intends to
* perform decompositions via compute(). This constructor
* can only be used if \p _MatrixType is a fixed-size matrix; use
* can only be used if \p MatrixType_ is a fixed-size matrix; use
* GeneralizedSelfAdjointEigenSolver(Index) for dynamic-size matrices.
*/
GeneralizedSelfAdjointEigenSolver() : Base() {}

12
libs/eigen/Eigen/src/Eigenvalues/HessenbergDecomposition.h
View File

@@ -11,6 +11,8 @@
#ifndef EIGEN_HESSENBERGDECOMPOSITION_H
#define EIGEN_HESSENBERGDECOMPOSITION_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
@@ -31,7 +33,7 @@ struct traits<HessenbergDecompositionMatrixHReturnType<MatrixType> >
*
* \brief Reduces a square matrix to Hessenberg form by an orthogonal similarity transformation
*
* \tparam _MatrixType the type of the matrix of which we are computing the Hessenberg decomposition
* \tparam MatrixType_ the type of the matrix of which we are computing the Hessenberg decomposition
*
* This class performs an Hessenberg decomposition of a matrix \f$ A \f$. In
* the real case, the Hessenberg decomposition consists of an orthogonal
@@ -54,12 +56,12 @@ struct traits<HessenbergDecompositionMatrixHReturnType<MatrixType> >
*
* \sa class ComplexSchur, class Tridiagonalization, \ref QR_Module "QR Module"
*/
template<typename _MatrixType> class HessenbergDecomposition
template<typename MatrixType_> class HessenbergDecomposition
{
public:
/** \brief Synonym for the template parameter \p _MatrixType. */
typedef _MatrixType MatrixType;
/** \brief Synonym for the template parameter \p MatrixType_. */
typedef MatrixType_ MatrixType;
enum {
Size = MatrixType::RowsAtCompileTime,
@@ -82,7 +84,7 @@ template<typename _MatrixType> class HessenbergDecomposition
typedef Matrix<Scalar, SizeMinusOne, 1, Options & ~RowMajor, MaxSizeMinusOne, 1> CoeffVectorType;
/** \brief Return type of matrixQ() */
typedef HouseholderSequence<MatrixType,typename internal::remove_all<typename CoeffVectorType::ConjugateReturnType>::type> HouseholderSequenceType;
typedef HouseholderSequence<MatrixType,internal::remove_all_t<typename CoeffVectorType::ConjugateReturnType>> HouseholderSequenceType;
typedef internal::HessenbergDecompositionMatrixHReturnType<MatrixType> MatrixHReturnType;

3
libs/eigen/Eigen/src/Eigenvalues/InternalHeaderCheck.h Normal file
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@@ -0,0 +1,3 @@
#ifndef EIGEN_EIGENVALUES_MODULE_H
#error "Please include Eigen/Eigenvalues instead of including headers inside the src directory directly."
#endif

2
libs/eigen/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h
View File

@@ -11,6 +11,8 @@
#ifndef EIGEN_MATRIXBASEEIGENVALUES_H
#define EIGEN_MATRIXBASEEIGENVALUES_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {

18
libs/eigen/Eigen/src/Eigenvalues/RealQZ.h
View File

@@ -10,6 +10,8 @@
#ifndef EIGEN_REAL_QZ_H
#define EIGEN_REAL_QZ_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \eigenvalues_module \ingroup Eigenvalues_Module
@@ -19,7 +21,7 @@ namespace Eigen {
*
* \brief Performs a real QZ decomposition of a pair of square matrices
*
* \tparam _MatrixType the type of the matrix of which we are computing the
* \tparam MatrixType_ the type of the matrix of which we are computing the
* real QZ decomposition; this is expected to be an instantiation of the
* Matrix class template.
*
@@ -54,10 +56,10 @@ namespace Eigen {
* \sa class RealSchur, class ComplexSchur, class EigenSolver, class ComplexEigenSolver
*/
template<typename _MatrixType> class RealQZ
template<typename MatrixType_> class RealQZ
{
public:
typedef _MatrixType MatrixType;
typedef MatrixType_ MatrixType;
enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
@@ -237,7 +239,7 @@ namespace Eigen {
for (Index i=dim-1; i>=j+2; i--) {
JRs G;
// kill S(i,j)
if(m_S.coeff(i,j) != 0)
if(!numext::is_exactly_zero(m_S.coeff(i, j)))
{
G.makeGivens(m_S.coeff(i-1,j), m_S.coeff(i,j), &m_S.coeffRef(i-1, j));
m_S.coeffRef(i,j) = Scalar(0.0);
@@ -248,7 +250,7 @@ namespace Eigen {
m_Q.applyOnTheRight(i-1,i,G);
}
// kill T(i,i-1)
if(m_T.coeff(i,i-1)!=Scalar(0))
if(!numext::is_exactly_zero(m_T.coeff(i, i - 1)))
{
G.makeGivens(m_T.coeff(i,i), m_T.coeff(i,i-1), &m_T.coeffRef(i,i));
m_T.coeffRef(i,i-1) = Scalar(0.0);
@@ -286,7 +288,7 @@ namespace Eigen {
while (res > 0)
{
Scalar s = abs(m_S.coeff(res-1,res-1)) + abs(m_S.coeff(res,res));
if (s == Scalar(0.0))
if (numext::is_exactly_zero(s))
s = m_normOfS;
if (abs(m_S.coeff(res,res-1)) < NumTraits<Scalar>::epsilon() * s)
break;
@@ -316,7 +318,7 @@ namespace Eigen {
using std::abs;
using std::sqrt;
const Index dim=m_S.cols();
if (abs(m_S.coeff(i+1,i))==Scalar(0))
if (numext::is_exactly_zero(abs(m_S.coeff(i + 1, i))))
return;
Index j = findSmallDiagEntry(i,i+1);
if (j==i-1)
@@ -627,7 +629,7 @@ namespace Eigen {
{
for(Index i=0; i<dim-1; ++i)
{
if(m_S.coeff(i+1, i) != Scalar(0))
if(!numext::is_exactly_zero(m_S.coeff(i + 1, i)))
{
JacobiRotation<Scalar> j_left, j_right;
internal::real_2x2_jacobi_svd(m_T, i, i+1, &j_left, &j_right);

14
libs/eigen/Eigen/src/Eigenvalues/RealSchur.h
View File

@@ -13,6 +13,8 @@
#include "./HessenbergDecomposition.h"
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \eigenvalues_module \ingroup Eigenvalues_Module
@@ -22,7 +24,7 @@ namespace Eigen {
*
* \brief Performs a real Schur decomposition of a square matrix
*
* \tparam _MatrixType the type of the matrix of which we are computing the
* \tparam MatrixType_ the type of the matrix of which we are computing the
* real Schur decomposition; this is expected to be an instantiation of the
* Matrix class template.
*
@@ -51,10 +53,10 @@ namespace Eigen {
*
* \sa class ComplexSchur, class EigenSolver, class ComplexEigenSolver
*/
template<typename _MatrixType> class RealSchur
template<typename MatrixType_> class RealSchur
{
public:
typedef _MatrixType MatrixType;
typedef MatrixType_ MatrixType;
enum {
RowsAtCompileTime = MatrixType::RowsAtCompileTime,
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
@@ -312,7 +314,7 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMa
Scalar considerAsZero = numext::maxi<Scalar>( norm * numext::abs2(NumTraits<Scalar>::epsilon()),
(std::numeric_limits<Scalar>::min)() );
if(norm!=Scalar(0))
if(!numext::is_exactly_zero(norm))
{
while (iu >= 0)
{
@@ -515,7 +517,7 @@ inline void RealSchur<MatrixType>::performFrancisQRStep(Index il, Index im, Inde
Matrix<Scalar, 2, 1> ess;
v.makeHouseholder(ess, tau, beta);
if (beta != Scalar(0)) // if v is not zero
if (!numext::is_exactly_zero(beta)) // if v is not zero
{
if (firstIteration && k > il)
m_matT.coeffRef(k,k-1) = -m_matT.coeff(k,k-1);
@@ -535,7 +537,7 @@ inline void RealSchur<MatrixType>::performFrancisQRStep(Index il, Index im, Inde
Matrix<Scalar, 1, 1> ess;
v.makeHouseholder(ess, tau, beta);
if (beta != Scalar(0)) // if v is not zero
if (!numext::is_exactly_zero(beta)) // if v is not zero
{
m_matT.coeffRef(iu-1, iu-2) = beta;
m_matT.block(iu-1, iu-1, 2, size-iu+1).applyHouseholderOnTheLeft(ess, tau, workspace);

2
libs/eigen/Eigen/src/Eigenvalues/RealSchur_LAPACKE.h
View File

@@ -33,6 +33,8 @@
#ifndef EIGEN_REAL_SCHUR_LAPACKE_H
#define EIGEN_REAL_SCHUR_LAPACKE_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \internal Specialization for the data types supported by LAPACKe */

44
libs/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
View File

@@ -13,9 +13,11 @@
#include "./Tridiagonalization.h"
#include "./InternalHeaderCheck.h"
namespace Eigen {
template<typename _MatrixType>
template<typename MatrixType_>
class GeneralizedSelfAdjointEigenSolver;
namespace internal {
@@ -33,7 +35,7 @@ ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag
*
* \brief Computes eigenvalues and eigenvectors of selfadjoint matrices
*
* \tparam _MatrixType the type of the matrix of which we are computing the
* \tparam MatrixType_ the type of the matrix of which we are computing the
* eigendecomposition; this is expected to be an instantiation of the Matrix
* class template.
*
@@ -73,11 +75,11 @@ ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag
*
* \sa MatrixBase::eigenvalues(), class EigenSolver, class ComplexEigenSolver
*/
template<typename _MatrixType> class SelfAdjointEigenSolver
template<typename MatrixType_> class SelfAdjointEigenSolver
{
public:
typedef _MatrixType MatrixType;
typedef MatrixType_ MatrixType;
enum {
Size = MatrixType::RowsAtCompileTime,
ColsAtCompileTime = MatrixType::ColsAtCompileTime,
@@ -85,13 +87,13 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
};
/** \brief Scalar type for matrices of type \p _MatrixType. */
/** \brief Scalar type for matrices of type \p MatrixType_. */
typedef typename MatrixType::Scalar Scalar;
typedef Eigen::Index Index; ///< \deprecated since Eigen 3.3
typedef Matrix<Scalar,Size,Size,ColMajor,MaxColsAtCompileTime,MaxColsAtCompileTime> EigenvectorsType;
/** \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
* \c double), and the type of the real part of \c Scalar if #Scalar is
@@ -104,7 +106,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
/** \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.
* The length of the vector is the size of \p MatrixType_.
*/
typedef typename internal::plain_col_type<MatrixType, RealScalar>::type RealVectorType;
typedef Tridiagonalization<MatrixType> TridiagonalizationType;
@@ -114,7 +116,7 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
*
* The default constructor is useful in cases in which the user intends to
* perform decompositions via compute(). This constructor
* can only be used if \p _MatrixType is a fixed-size matrix; use
* can only be used if \p MatrixType_ is a fixed-size matrix; use
* SelfAdjointEigenSolver(Index) for dynamic-size matrices.
*
* Example: \include SelfAdjointEigenSolver_SelfAdjointEigenSolver.cpp
@@ -372,12 +374,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
static const int m_maxIterations = 30;
protected:
static EIGEN_DEVICE_FUNC
void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
EigenvectorsType m_eivec;
RealVectorType m_eivalues;
typename TridiagonalizationType::SubDiagonalType m_subdiag;
@@ -419,10 +417,8 @@ EIGEN_DEVICE_FUNC
SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
::compute(const EigenBase<InputType>& a_matrix, int options)
{
check_template_parameters();
const InputType &matrix(a_matrix.derived());
EIGEN_USING_STD(abs);
eigen_assert(matrix.cols() == matrix.rows());
eigen_assert((options&~(EigVecMask|GenEigMask))==0
@@ -451,7 +447,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
// map the matrix coefficients to [-1:1] to avoid over- and underflow.
mat = matrix.template triangularView<Lower>();
RealScalar scale = mat.cwiseAbs().maxCoeff();
if(scale==RealScalar(0)) scale = RealScalar(1);
if(numext::is_exactly_zero(scale)) scale = RealScalar(1);
mat.template triangularView<Lower>() /= scale;
m_subdiag.resize(n-1);
m_hcoeffs.resize(n-1);
@@ -530,7 +526,7 @@ ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag
}
// find the largest unreduced block at the end of the matrix.
while (end>0 && subdiag[end-1]==RealScalar(0))
while (end>0 && numext::is_exactly_zero(subdiag[end - 1]))
{
end--;
}
@@ -542,7 +538,7 @@ ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag
if(iter > maxIterations * n) break;
start = end - 1;
while (start>0 && subdiag[start-1]!=0)
while (start>0 && !numext::is_exactly_zero(subdiag[start - 1]))
start--;
internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(diag.data(), subdiag.data(), start, end, computeEigenvectors ? eivec.data() : (Scalar*)0, n);
@@ -847,12 +843,12 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
// RealScalar mu = diag[end] - e2 / (td + (td>0 ? 1 : -1) * sqrt(td*td + e2));
// This explain the following, somewhat more complicated, version:
RealScalar mu = diag[end];
if(td==RealScalar(0)) {
if(numext::is_exactly_zero(td)) {
mu -= numext::abs(e);
} else if (e != RealScalar(0)) {
} else if (!numext::is_exactly_zero(e)) {
const RealScalar e2 = numext::abs2(e);
const RealScalar h = numext::hypot(td,e);
if(e2 == RealScalar(0)) {
if(numext::is_exactly_zero(e2)) {
mu -= e / ((td + (td>RealScalar(0) ? h : -h)) / e);
} else {
mu -= e2 / (td + (td>RealScalar(0) ? h : -h));
@@ -863,7 +859,7 @@ static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index sta
RealScalar z = subdiag[start];
// If z ever becomes zero, the Givens rotation will be the identity and
// z will stay zero for all future iterations.
for (Index k = start; k < end && z != RealScalar(0); ++k)
for (Index k = start; k < end && !numext::is_exactly_zero(z); ++k)
{
JacobiRotation<RealScalar> rot;
rot.makeGivens(x, z);

2
libs/eigen/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h
View File

@@ -33,6 +33,8 @@
#ifndef EIGEN_SAEIGENSOLVER_LAPACKE_H
#define EIGEN_SAEIGENSOLVER_LAPACKE_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
/** \internal Specialization for the data types supported by LAPACKe */

29
libs/eigen/Eigen/src/Eigenvalues/Tridiagonalization.h
View File

@@ -11,6 +11,8 @@
#ifndef EIGEN_TRIDIAGONALIZATION_H
#define EIGEN_TRIDIAGONALIZATION_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
@@ -36,7 +38,7 @@ void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs);
*
* \brief Tridiagonal decomposition of a selfadjoint matrix
*
* \tparam _MatrixType the type of the matrix of which we are computing the
* \tparam 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.
*
@@ -61,12 +63,12 @@ void tridiagonalization_inplace(MatrixType& matA, CoeffVectorType& hCoeffs);
*
* \sa class HessenbergDecomposition, class SelfAdjointEigenSolver
*/
template<typename _MatrixType> class Tridiagonalization
template<typename MatrixType_> class Tridiagonalization
{
public:
/** \brief Synonym for the template parameter \p _MatrixType. */
typedef _MatrixType MatrixType;
/** \brief Synonym for the template parameter \p MatrixType_. */
typedef MatrixType_ MatrixType;
typedef typename MatrixType::Scalar Scalar;
typedef typename NumTraits<Scalar>::Real RealScalar;
@@ -83,21 +85,21 @@ template<typename _MatrixType> class Tridiagonalization
typedef Matrix<Scalar, SizeMinusOne, 1, Options & ~RowMajor, MaxSizeMinusOne, 1> CoeffVectorType;
typedef typename internal::plain_col_type<MatrixType, RealScalar>::type DiagonalType;
typedef Matrix<RealScalar, SizeMinusOne, 1, Options & ~RowMajor, MaxSizeMinusOne, 1> SubDiagonalType;
typedef typename internal::remove_all<typename MatrixType::RealReturnType>::type MatrixTypeRealView;
typedef internal::remove_all_t<typename MatrixType::RealReturnType> MatrixTypeRealView;
typedef internal::TridiagonalizationMatrixTReturnType<MatrixTypeRealView> MatrixTReturnType;
typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
typename internal::add_const_on_value_type<typename Diagonal<const MatrixType>::RealReturnType>::type,
typedef std::conditional_t<NumTraits<Scalar>::IsComplex,
internal::add_const_on_value_type_t<typename Diagonal<const MatrixType>::RealReturnType>,
const Diagonal<const MatrixType>
>::type DiagonalReturnType;
> DiagonalReturnType;
typedef typename internal::conditional<NumTraits<Scalar>::IsComplex,
typename internal::add_const_on_value_type<typename Diagonal<const MatrixType, -1>::RealReturnType>::type,
typedef std::conditional_t<NumTraits<Scalar>::IsComplex,
internal::add_const_on_value_type_t<typename Diagonal<const MatrixType, -1>::RealReturnType>,
const Diagonal<const MatrixType, -1>
>::type SubDiagonalReturnType;
> SubDiagonalReturnType;
/** \brief Return type of matrixQ() */
typedef HouseholderSequence<MatrixType,typename internal::remove_all<typename CoeffVectorType::ConjugateReturnType>::type> HouseholderSequenceType;
typedef HouseholderSequence<MatrixType,internal::remove_all_t<typename CoeffVectorType::ConjugateReturnType>> HouseholderSequenceType;
/** \brief Default constructor.
*
@@ -440,9 +442,8 @@ void tridiagonalization_inplace(MatrixType& mat, DiagonalType& diag, SubDiagonal
template<typename MatrixType, int Size, bool IsComplex>
struct tridiagonalization_inplace_selector
{
typedef typename Tridiagonalization<MatrixType>::CoeffVectorType CoeffVectorType;
typedef typename Tridiagonalization<MatrixType>::HouseholderSequenceType HouseholderSequenceType;
template<typename DiagonalType, typename SubDiagonalType>
template<typename DiagonalType, typename SubDiagonalType, typename CoeffVectorType>
static EIGEN_DEVICE_FUNC
void run(MatrixType& mat, DiagonalType& diag, SubDiagonalType& subdiag, CoeffVectorType& hCoeffs, bool extractQ)
{