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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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66
libs/eigen/Eigen/src/QR/ColPivHouseholderQR.h
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@@ -11,11 +11,13 @@
#ifndef EIGEN_COLPIVOTINGHOUSEHOLDERQR_H
#define EIGEN_COLPIVOTINGHOUSEHOLDERQR_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
namespace internal {
template<typename _MatrixType> struct traits<ColPivHouseholderQR<_MatrixType> >
: traits<_MatrixType>
template<typename MatrixType_> struct traits<ColPivHouseholderQR<MatrixType_> >
: traits<MatrixType_>
{
typedef MatrixXpr XprKind;
typedef SolverStorage StorageKind;
@@ -31,7 +33,7 @@ template<typename _MatrixType> struct traits<ColPivHouseholderQR<_MatrixType> >
*
* \brief Householder rank-revealing QR decomposition of a matrix with column-pivoting
*
* \tparam _MatrixType the type of the matrix of which we are computing the QR decomposition
* \tparam MatrixType_ the type of the matrix of which we are computing the QR decomposition
*
* This class performs a rank-revealing QR decomposition of a matrix \b A into matrices \b P, \b Q and \b R
* such that
@@ -48,12 +50,12 @@ template<typename _MatrixType> struct traits<ColPivHouseholderQR<_MatrixType> >
*
* \sa MatrixBase::colPivHouseholderQr()
*/
template<typename _MatrixType> class ColPivHouseholderQR
: public SolverBase<ColPivHouseholderQR<_MatrixType> >
template<typename MatrixType_> class ColPivHouseholderQR
: public SolverBase<ColPivHouseholderQR<MatrixType_> >
{
public:
typedef _MatrixType MatrixType;
typedef MatrixType_ MatrixType;
typedef SolverBase<ColPivHouseholderQR> Base;
friend class SolverBase<ColPivHouseholderQR>;
@@ -67,7 +69,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
typedef typename internal::plain_row_type<MatrixType, Index>::type IntRowVectorType;
typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
typedef typename internal::plain_row_type<MatrixType, RealScalar>::type RealRowVectorType;
typedef HouseholderSequence<MatrixType,typename internal::remove_all<typename HCoeffsType::ConjugateReturnType>::type> HouseholderSequenceType;
typedef HouseholderSequence<MatrixType,internal::remove_all_t<typename HCoeffsType::ConjugateReturnType>> HouseholderSequenceType;
typedef typename MatrixType::PlainObject PlainObject;
private:
@@ -217,6 +219,21 @@ template<typename _MatrixType> class ColPivHouseholderQR
return m_colsPermutation;
}
/** \returns the determinant of the matrix of which
* *this is the QR decomposition. It has only linear complexity
* (that is, O(n) where n is the dimension of the square matrix)
* as the QR decomposition has already been computed.
*
* \note This is only for square matrices.
*
* \warning a determinant can be very big or small, so for matrices
* of large enough dimension, there is a risk of overflow/underflow.
* One way to work around that is to use logAbsDeterminant() instead.
*
* \sa absDeterminant(), logAbsDeterminant(), MatrixBase::determinant()
*/
typename MatrixType::Scalar determinant() const;
/** \returns the absolute value of the determinant of the matrix of which
* *this is the QR decomposition. It has only linear complexity
* (that is, O(n) where n is the dimension of the square matrix)
@@ -228,7 +245,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
* of large enough dimension, there is a risk of overflow/underflow.
* One way to work around that is to use logAbsDeterminant() instead.
*
* \sa logAbsDeterminant(), MatrixBase::determinant()
* \sa determinant(), logAbsDeterminant(), MatrixBase::determinant()
*/
typename MatrixType::RealScalar absDeterminant() const;
@@ -242,7 +259,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
* \note This method is useful to work around the risk of overflow/underflow that's inherent
* to determinant computation.
*
* \sa absDeterminant(), MatrixBase::determinant()
* \sa determinant(), absDeterminant(), MatrixBase::determinant()
*/
typename MatrixType::RealScalar logAbsDeterminant() const;
@@ -426,10 +443,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
friend class CompleteOrthogonalDecomposition<MatrixType>;
static void check_template_parameters()
{
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar);
}
EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar)
void computeInPlace();
@@ -443,9 +457,19 @@ template<typename _MatrixType> class ColPivHouseholderQR
bool m_isInitialized, m_usePrescribedThreshold;
RealScalar m_prescribedThreshold, m_maxpivot;
Index m_nonzero_pivots;
Index m_det_pq;
Index m_det_p;
};
template<typename MatrixType>
typename MatrixType::Scalar ColPivHouseholderQR<MatrixType>::determinant() const
{
eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
eigen_assert(m_qr.rows() == m_qr.cols() && "You can't take the determinant of a non-square matrix!");
Scalar detQ;
internal::householder_determinant<HCoeffsType, Scalar, NumTraits<Scalar>::IsComplex>::run(m_hCoeffs, detQ);
return m_qr.diagonal().prod() * detQ * Scalar(m_det_p);
}
template<typename MatrixType>
typename MatrixType::RealScalar ColPivHouseholderQR<MatrixType>::absDeterminant() const
{
@@ -481,8 +505,6 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
template<typename MatrixType>
void ColPivHouseholderQR<MatrixType>::computeInPlace()
{
check_template_parameters();
// the column permutation is stored as int indices, so just to be sure:
eigen_assert(m_qr.cols()<=NumTraits<int>::highest());
@@ -555,7 +577,7 @@ void ColPivHouseholderQR<MatrixType>::computeInPlace()
// http://www.netlib.org/lapack/lawnspdf/lawn176.pdf
// and used in LAPACK routines xGEQPF and xGEQP3.
// See lines 278-297 in http://www.netlib.org/lapack/explore-html/dc/df4/sgeqpf_8f_source.html
if (m_colNormsUpdated.coeffRef(j) != RealScalar(0)) {
if (!numext::is_exactly_zero(m_colNormsUpdated.coeffRef(j))) {
RealScalar temp = abs(m_qr.coeffRef(k, j)) / m_colNormsUpdated.coeffRef(j);
temp = (RealScalar(1) + temp) * (RealScalar(1) - temp);
temp = temp < RealScalar(0) ? RealScalar(0) : temp;
@@ -577,14 +599,14 @@ void ColPivHouseholderQR<MatrixType>::computeInPlace()
for(PermIndexType k = 0; k < size/*m_nonzero_pivots*/; ++k)
m_colsPermutation.applyTranspositionOnTheRight(k, PermIndexType(m_colsTranspositions.coeff(k)));
m_det_pq = (number_of_transpositions%2) ? -1 : 1;
m_det_p = (number_of_transpositions%2) ? -1 : 1;
m_isInitialized = true;
}
#ifndef EIGEN_PARSED_BY_DOXYGEN
template<typename _MatrixType>
template<typename MatrixType_>
template<typename RhsType, typename DstType>
void ColPivHouseholderQR<_MatrixType>::_solve_impl(const RhsType &rhs, DstType &dst) const
void ColPivHouseholderQR<MatrixType_>::_solve_impl(const RhsType &rhs, DstType &dst) const
{
const Index nonzero_pivots = nonzeroPivots();
@@ -606,9 +628,9 @@ void ColPivHouseholderQR<_MatrixType>::_solve_impl(const RhsType &rhs, DstType &
for(Index i = nonzero_pivots; i < cols(); ++i) dst.row(m_colsPermutation.indices().coeff(i)).setZero();
}
template<typename _MatrixType>
template<typename MatrixType_>
template<bool Conjugate, typename RhsType, typename DstType>
void ColPivHouseholderQR<_MatrixType>::_solve_impl_transposed(const RhsType &rhs, DstType &dst) const
void ColPivHouseholderQR<MatrixType_>::_solve_impl_transposed(const RhsType &rhs, DstType &dst) const
{
const Index nonzero_pivots = nonzeroPivots();