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    7 #ifndef SPECTRA_SPARSE_REGULAR_INVERSE_H 
    8 #define SPECTRA_SPARSE_REGULAR_INVERSE_H 
   11 #include <Eigen/SparseCore> 
   12 #include <Eigen/IterativeLinearSolvers> 
   36 template <
typename Scalar_, 
int Uplo = Eigen::Lower, 
int Flags = Eigen::ColMajor, 
typename StorageIndex = 
int>
 
   66     template <
typename Derived>
 
   72             "SparseRegularInverse: the \"Flags\" template parameter does not match the input matrix (Eigen::ColMajor/Eigen::RowMajor)");
 
   74         if (
mat.rows() != 
mat.cols())
 
   75             throw std::invalid_argument(
"SparseRegularInverse: matrix must be square");
 
  109         y.noalias() = 
m_cg.solve(
x);
 
  115             throw std::runtime_error(
"SparseRegularInverse: CG solver does not converge");
 
  129         y.noalias() = 
m_mat.template selfadjointView<Uplo>() * 
x;
 
  135 #endif  // SPECTRA_SPARSE_REGULAR_INVERSE_H 
  
A versatible sparse matrix representation.
@ Successful
Computation was successful.
SparseRegularInverse(const Eigen::SparseMatrixBase< Derived > &mat)
void perform_op(const Scalar *x_in, Scalar *y_out) const
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A conjugate gradient solver for sparse (or dense) self-adjoint problems.
void solve(const Scalar *x_in, Scalar *y_out) const
Eigen::ConjugateGradient< SparseMatrix > m_cg
A matrix or vector expression mapping an existing array of data.
Base class of any sparse matrices or sparse expressions.
ConstGenericSparseMatrix m_mat
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
gtsam
Author(s): 
autogenerated on Wed May 28 2025 03:03:43