henry/SimCore
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

ADD: added other eigen lib

Browse Source
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
Download Patch File Download Diff File Expand all files Collapse all files

3
libs/eigen/Eigen/src/SPQRSupport/InternalHeaderCheck.h Normal file
View File

@@ -0,0 +1,3 @@
#ifndef EIGEN_SPQRSUPPORT_MODULE_H
#error "Please include Eigen/SPQRSupport instead of including headers inside the src directory directly."
#endif

30
libs/eigen/Eigen/src/SPQRSupport/SuiteSparseQRSupport.h
View File

@@ -11,6 +11,8 @@
#ifndef EIGEN_SUITESPARSEQRSUPPORT_H
#define EIGEN_SUITESPARSEQRSUPPORT_H
#include "./InternalHeaderCheck.h"
namespace Eigen {
template<typename MatrixType> class SPQR;
@@ -50,21 +52,21 @@ namespace Eigen {
* R is the sparse triangular factor. Use matrixQR() to get it as SparseMatrix.
* NOTE : The Index type of R is always SuiteSparse_long. You can get it with SPQR::Index
*
* \tparam _MatrixType The type of the sparse matrix A, must be a column-major SparseMatrix<>
* \tparam MatrixType_ The type of the sparse matrix A, must be a column-major SparseMatrix<>
*
* \implsparsesolverconcept
*
*
*/
template<typename _MatrixType>
class SPQR : public SparseSolverBase<SPQR<_MatrixType> >
template<typename MatrixType_>
class SPQR : public SparseSolverBase<SPQR<MatrixType_> >
{
protected:
typedef SparseSolverBase<SPQR<_MatrixType> > Base;
typedef SparseSolverBase<SPQR<MatrixType_> > Base;
using Base::m_isInitialized;
public:
typedef typename _MatrixType::Scalar Scalar;
typedef typename _MatrixType::RealScalar RealScalar;
typedef typename MatrixType_::Scalar Scalar;
typedef typename MatrixType_::RealScalar RealScalar;
typedef SuiteSparse_long StorageIndex ;
typedef SparseMatrix<Scalar, ColMajor, StorageIndex> MatrixType;
typedef Map<PermutationMatrix<Dynamic, Dynamic, StorageIndex> > PermutationType;
@@ -90,7 +92,7 @@ class SPQR : public SparseSolverBase<SPQR<_MatrixType> >
cholmod_l_start(&m_cc);
}
explicit SPQR(const _MatrixType& matrix)
explicit SPQR(const MatrixType_& matrix)
: m_analysisIsOk(false),
m_factorizationIsOk(false),
m_isRUpToDate(false),
@@ -122,7 +124,7 @@ class SPQR : public SparseSolverBase<SPQR<_MatrixType> >
std::free(m_HPinv);
}
void compute(const _MatrixType& matrix)
void compute(const MatrixType_& matrix)
{
if(m_isInitialized) SPQR_free();
@@ -137,7 +139,7 @@ class SPQR : public SparseSolverBase<SPQR<_MatrixType> >
{
RealScalar max2Norm = 0.0;
for (int j = 0; j < mat.cols(); j++) max2Norm = numext::maxi(max2Norm, mat.col(j).norm());
if(max2Norm==RealScalar(0))
if(numext::is_exactly_zero(max2Norm))
max2Norm = RealScalar(1);
pivotThreshold = 20 * (mat.rows() + mat.cols()) * max2Norm * NumTraits<RealScalar>::epsilon();
}
@@ -258,12 +260,12 @@ class SPQR : public SparseSolverBase<SPQR<_MatrixType> >
int m_ordering; // Ordering method to use, see SPQR's manual
int m_allow_tol; // Allow to use some tolerance during numerical factorization.
RealScalar m_tolerance; // treat columns with 2-norm below this tolerance as zero
mutable cholmod_sparse *m_cR; // The sparse R factor in cholmod format
mutable cholmod_sparse *m_cR = nullptr; // The sparse R factor in cholmod format
mutable MatrixType m_R; // The sparse matrix R in Eigen format
mutable StorageIndex *m_E; // The permutation applied to columns
mutable cholmod_sparse *m_H; //The householder vectors
mutable StorageIndex *m_HPinv; // The row permutation of H
mutable cholmod_dense *m_HTau; // The Householder coefficients
mutable StorageIndex *m_E = nullptr; // The permutation applied to columns
mutable cholmod_sparse *m_H = nullptr; //The householder vectors
mutable StorageIndex *m_HPinv = nullptr; // The row permutation of H
mutable cholmod_dense *m_HTau = nullptr; // The Householder coefficients
mutable Index m_rank; // The rank of the matrix
mutable cholmod_common m_cc; // Workspace and parameters
bool m_useDefaultThreshold; // Use default threshold