Stan Math Library  2.14.0
reverse mode automatic differentiation
Public Types | Public Member Functions | Public Attributes | List of all members
stan::math::LDLT_factor< T, R, C > Class Template Reference

LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodiff of things like log determinants and solutions to linear systems. More...

#include <LDLT_factor.hpp>

Public Types

typedef size_t size_type
 
typedef double value_type
 

Public Member Functions

 LDLT_factor ()
 
 LDLT_factor (const Eigen::Matrix< T, R, C > &A)
 
void compute (const Eigen::Matrix< T, R, C > &A)
 
bool success () const
 
log_abs_det () const
 
void inverse (Eigen::Matrix< T, R, C > &invA) const
 
template<typename Rhs >
const Eigen::internal::solve_retval< Eigen::LDLT< Eigen::Matrix< T, R, C > >, Rhs > solve (const Eigen::MatrixBase< Rhs > &b) const
 
Eigen::Matrix< T, R, C > solveRight (const Eigen::Matrix< T, R, C > &B) const
 
Eigen::Matrix< T, Eigen::Dynamic, 1 > vectorD () const
 
Eigen::LDLT< Eigen::Matrix< T, R, C > > matrixLDLT () const
 
size_t rows () const
 
size_t cols () const
 

Public Attributes

size_t N_
 
boost::shared_ptr< Eigen::LDLT< Eigen::Matrix< T, R, C > > > ldltP_
 

Detailed Description

template<int R, int C, typename T>
class stan::math::LDLT_factor< T, R, C >

LDLT_factor is a thin wrapper on Eigen::LDLT to allow for reusing factorizations and efficient autodiff of things like log determinants and solutions to linear systems.

After the constructor and/or compute() is called users of LDLT_factor are responsible for calling success() to check whether the factorization has succeeded. Use of an LDLT_factor object (e.g., in mdivide_left_ldlt) is undefined if success() is false.

It's usage pattern is:

Eigen::Matrix<T, R, C> A1, A2;
LDLT_factor<T, R, C> ldlt_A1(A1);
LDLT_factor<T, R, C> ldlt_A2;
ldlt_A2.compute(A2);

Now, the caller should check that ldlt_A1.success() and ldlt_A2.success() are true or abort accordingly. Alternatively, call check_ldlt_factor().

Note that ldlt_A1 and ldlt_A2 are completely equivalent. They simply demonstrate two different ways to construct the factorization.

Now, the caller can use the LDLT_factor objects as needed. For instance

x1 = mdivide_left_ldlt(ldlt_A1, b1);
x2 = mdivide_right_ldlt(b2, ldlt_A2);
d1 = log_determinant_ldlt(ldlt_A1);
d2 = log_determinant_ldlt(ldlt_A2);

This class is conceptually similar to the corresponding Eigen class Any spd matrix A can be decomposed as LDL' where L is unit lower-triangular and D is diagonal with positive diagonal elements

Definition at line 56 of file LDLT_factor.hpp.

Member Typedef Documentation

§ size_type

template<int R, int C, typename T >
typedef size_t stan::math::LDLT_factor< T, R, C >::size_type

Definition at line 125 of file LDLT_factor.hpp.

§ value_type

template<int R, int C, typename T >
typedef double stan::math::LDLT_factor< T, R, C >::value_type

Definition at line 126 of file LDLT_factor.hpp.

Constructor & Destructor Documentation

§ LDLT_factor() [1/2]

template<int R, int C, typename T >
stan::math::LDLT_factor< T, R, C >::LDLT_factor ( )
inline

Definition at line 58 of file LDLT_factor.hpp.

§ LDLT_factor() [2/2]

template<int R, int C, typename T >
stan::math::LDLT_factor< T, R, C >::LDLT_factor ( const Eigen::Matrix< T, R, C > &  A)
inlineexplicit

Definition at line 61 of file LDLT_factor.hpp.

Member Function Documentation

§ cols()

template<int R, int C, typename T >
size_t stan::math::LDLT_factor< T, R, C >::cols ( ) const
inline

Definition at line 123 of file LDLT_factor.hpp.

§ compute()

template<int R, int C, typename T >
void stan::math::LDLT_factor< T, R, C >::compute ( const Eigen::Matrix< T, R, C > &  A)
inline

Definition at line 66 of file LDLT_factor.hpp.

§ inverse()

template<int R, int C, typename T >
void stan::math::LDLT_factor< T, R, C >::inverse ( Eigen::Matrix< T, R, C > &  invA) const
inline

Definition at line 88 of file LDLT_factor.hpp.

§ log_abs_det()

template<int R, int C, typename T >
T stan::math::LDLT_factor< T, R, C >::log_abs_det ( ) const
inline

Definition at line 84 of file LDLT_factor.hpp.

§ matrixLDLT()

template<int R, int C, typename T >
Eigen::LDLT<Eigen::Matrix<T, R, C> > stan::math::LDLT_factor< T, R, C >::matrixLDLT ( ) const
inline

Definition at line 118 of file LDLT_factor.hpp.

§ rows()

template<int R, int C, typename T >
size_t stan::math::LDLT_factor< T, R, C >::rows ( ) const
inline

Definition at line 122 of file LDLT_factor.hpp.

§ solve()

template<int R, int C, typename T >
template<typename Rhs >
const Eigen::internal::solve_retval<Eigen::LDLT< Eigen::Matrix<T, R, C> >, Rhs> stan::math::LDLT_factor< T, R, C >::solve ( const Eigen::MatrixBase< Rhs > &  b) const
inline

Definition at line 104 of file LDLT_factor.hpp.

§ solveRight()

template<int R, int C, typename T >
Eigen::Matrix<T, R, C> stan::math::LDLT_factor< T, R, C >::solveRight ( const Eigen::Matrix< T, R, C > &  B) const
inline

Definition at line 110 of file LDLT_factor.hpp.

§ success()

template<int R, int C, typename T >
bool stan::math::LDLT_factor< T, R, C >::success ( ) const
inline

Definition at line 72 of file LDLT_factor.hpp.

§ vectorD()

template<int R, int C, typename T >
Eigen::Matrix<T, Eigen::Dynamic, 1> stan::math::LDLT_factor< T, R, C >::vectorD ( ) const
inline

Definition at line 114 of file LDLT_factor.hpp.

Member Data Documentation

§ ldltP_

template<int R, int C, typename T >
boost::shared_ptr<Eigen::LDLT<Eigen::Matrix<T, R, C> > > stan::math::LDLT_factor< T, R, C >::ldltP_

Definition at line 129 of file LDLT_factor.hpp.

§ N_

template<int R, int C, typename T >
size_t stan::math::LDLT_factor< T, R, C >::N_

Definition at line 128 of file LDLT_factor.hpp.


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

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