slp::SparseRegularizedLDLT< Scalar > Class Template Reference

#include </home/runner/work/Sleipnir/Sleipnir/include/sleipnir/optimization/solver/util/sparse_regularized_ldlt.hpp>

Public Types
using	DenseVector = Eigen::Vector< Scalar, Eigen::Dynamic >
	Type alias for dense vector.
using	SparseMatrix = Eigen::SparseMatrix< Scalar >
	Type alias for sparse matrix.

Public Member Functions
	SparseRegularizedLDLT (int num_decision_variables, int num_equality_constraints)
	SparseRegularizedLDLT (int num_decision_variables, int num_equality_constraints, Scalar γ_min)
Eigen::ComputationInfo	info () const
SparseRegularizedLDLT &	compute (const SparseMatrix &lhs)
template<typename Rhs >
DenseVector	solve (const Eigen::MatrixBase< Rhs > &rhs) const
template<typename Rhs >
DenseVector	solve (const Eigen::SparseMatrixBase< Rhs > &rhs) const
Scalar	hessian_regularization () const
Scalar	constraint_jacobian_regularization () const

Detailed Description

template<typename Scalar>
class slp::SparseRegularizedLDLT< Scalar >

Solves sparse systems of linear equations using a regularized LDLT factorization.

Template Parameters

Scalar

Scalar type.

Constructor & Destructor Documentation

SparseRegularizedLDLT() [1/2]

template<typename Scalar >

slp::SparseRegularizedLDLT< Scalar >::SparseRegularizedLDLT ( int  num_decision_variables, int  num_equality_constraints  )

inline

Constructs a SparseRegularizedLDLT instance.

Parameters

num_decision_variables	The number of decision variables in the system.
num_equality_constraints	The number of equality constraints in the system.

SparseRegularizedLDLT() [2/2]

template<typename Scalar >

slp::SparseRegularizedLDLT< Scalar >::SparseRegularizedLDLT ( int  num_decision_variables, int  num_equality_constraints, Scalar  γ_min  )

inline

Constructs a SparseRegularizedLDLT instance.

Parameters

num_decision_variables	The number of decision variables in the system.
num_equality_constraints	The number of equality constraints in the system.
γ_min	The minimum constraint regularization.

Member Function Documentation

compute()

template<typename Scalar >

SparseRegularizedLDLT & slp::SparseRegularizedLDLT< Scalar >::compute ( const SparseMatrix &  lhs )

inline

Computes the regularized LDLT factorization of a matrix.

The matrix's symbolic decomposition is reused in subsequent calls, so subsequent calls must be given a matrix with the same sparsity pattern.

Parameters

lhs	Left-hand side of the system.

Returns

The factorization.

constraint_jacobian_regularization()

template<typename Scalar >

Scalar slp::SparseRegularizedLDLT< Scalar >::constraint_jacobian_regularization ( ) const

inline

Returns the constraint Jacobian regularization factor.

Returns

Constraint Jacobian regularization factor.

hessian_regularization()

template<typename Scalar >

Scalar slp::SparseRegularizedLDLT< Scalar >::hessian_regularization ( ) const

inline

Returns the Hessian regularization factor.

Returns

Hessian regularization factor.

info()

template<typename Scalar >

Eigen::ComputationInfo slp::SparseRegularizedLDLT< Scalar >::info ( ) const

inline

Reports whether previous computation was successful.

Returns

Whether previous computation was successful.

solve() [1/2]

template<typename Scalar >

template<typename Rhs >

DenseVector slp::SparseRegularizedLDLT< Scalar >::solve ( const Eigen::MatrixBase< Rhs > &  rhs ) const

inline

Solves the system of equations using a regularized LDLT factorization.

Parameters

rhs	Right-hand side of the system.

Returns

The solution.

solve() [2/2]

template<typename Scalar >

template<typename Rhs >

DenseVector slp::SparseRegularizedLDLT< Scalar >::solve ( const Eigen::SparseMatrixBase< Rhs > &  rhs ) const

inline

Solves the system of equations using a regularized LDLT factorization.

Parameters

rhs	Right-hand side of the system.

Returns

The solution.

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The documentation for this class was generated from the following file:

• /home/runner/work/Sleipnir/Sleipnir/include/sleipnir/optimization/solver/util/sparse_regularized_ldlt.hpp