WPILibC++ 2023.4.3
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Modified Incomplete Cholesky with dual threshold. More...
Public Types | |
enum | { UpLo = _UpLo } |
enum | { ColsAtCompileTime = Dynamic , MaxColsAtCompileTime = Dynamic } |
typedef NumTraits< Scalar >::Real | RealScalar |
typedef _OrderingType | OrderingType |
typedef OrderingType::PermutationType | PermutationType |
typedef PermutationType::StorageIndex | StorageIndex |
typedef SparseMatrix< Scalar, ColMajor, StorageIndex > | FactorType |
typedef Matrix< Scalar, Dynamic, 1 > | VectorSx |
typedef Matrix< RealScalar, Dynamic, 1 > | VectorRx |
typedef Matrix< StorageIndex, Dynamic, 1 > | VectorIx |
typedef std::vector< std::list< StorageIndex > > | VectorList |
Public Member Functions | |
IncompleteCholesky () | |
Default constructor leaving the object in a partly non-initialized stage. More... | |
template<typename MatrixType > | |
IncompleteCholesky (const MatrixType &matrix) | |
Constructor computing the incomplete factorization for the given matrix matrix. More... | |
EIGEN_CONSTEXPR Index | rows () const EIGEN_NOEXCEPT |
EIGEN_CONSTEXPR Index | cols () const EIGEN_NOEXCEPT |
ComputationInfo | info () const |
Reports whether previous computation was successful. More... | |
void | setInitialShift (RealScalar shift) |
Set the initial shift parameter \( \sigma \). More... | |
template<typename MatrixType > | |
void | analyzePattern (const MatrixType &mat) |
Computes the fill reducing permutation vector using the sparsity pattern of mat. More... | |
template<typename MatrixType > | |
void | factorize (const MatrixType &mat) |
Performs the numerical factorization of the input matrix mat. More... | |
template<typename MatrixType > | |
void | compute (const MatrixType &mat) |
Computes or re-computes the incomplete Cholesky factorization of the input matrix mat. More... | |
template<typename Rhs , typename Dest > | |
void | _solve_impl (const Rhs &b, Dest &x) const |
const FactorType & | matrixL () const |
const VectorRx & | scalingS () const |
const PermutationType & | permutationP () const |
template<typename _MatrixType > | |
void | factorize (const _MatrixType &mat) |
Public Member Functions inherited from Eigen::SparseSolverBase< IncompleteCholesky< Scalar, Lower, AMDOrdering< int > > > | |
SparseSolverBase () | |
Default constructor. More... | |
~SparseSolverBase () | |
IncompleteCholesky< Scalar, Lower, AMDOrdering< int > > & | derived () |
const IncompleteCholesky< Scalar, Lower, AMDOrdering< int > > & | derived () const |
const Solve< IncompleteCholesky< Scalar, Lower, AMDOrdering< int > >, Rhs > | solve (const MatrixBase< Rhs > &b) const |
const Solve< IncompleteCholesky< Scalar, Lower, AMDOrdering< int > >, Rhs > | solve (const SparseMatrixBase< Rhs > &b) const |
void | _solve_impl (const SparseMatrixBase< Rhs > &b, SparseMatrixBase< Dest > &dest) const |
Protected Types | |
typedef SparseSolverBase< IncompleteCholesky< Scalar, _UpLo, _OrderingType > > | Base |
Protected Attributes | |
FactorType | m_L |
VectorRx | m_scale |
RealScalar | m_initialShift |
bool | m_analysisIsOk |
bool | m_factorizationIsOk |
ComputationInfo | m_info |
PermutationType | m_perm |
bool | m_isInitialized |
Protected Attributes inherited from Eigen::SparseSolverBase< IncompleteCholesky< Scalar, Lower, AMDOrdering< int > > > | |
bool | m_isInitialized |
Modified Incomplete Cholesky with dual threshold.
References : C-J. Lin and J. J. Moré, Incomplete Cholesky Factorizations with Limited memory, SIAM J. Sci. Comput. 21(1), pp. 24-45, 1999
Scalar | the scalar type of the input matrices |
_UpLo | The triangular part that will be used for the computations. It can be Lower or Upper. Default is Lower. |
_OrderingType | The ordering method to use, either AMDOrdering<> or NaturalOrdering<>. Default is AMDOrdering<int>, unless EIGEN_MPL2_ONLY is defined, in which case the default is NaturalOrdering<int>. |
\implsparsesolverconcept
It performs the following incomplete factorization: \( S P A P' S \approx L L' \) where L is a lower triangular factor, S is a diagonal scaling matrix, and P is a fill-in reducing permutation as computed by the ordering method.
Shifting strategy: Let \( B = S P A P' S \) be the scaled matrix on which the factorization is carried out, and \( \beta \) be the minimum value of the diagonal. If \( \beta > 0 \) then, the factorization is directly performed on the matrix B. Otherwise, the factorization is performed on the shifted matrix \( B + (\sigma+|\beta| I \) where \( \sigma \) is the initial shift value as returned and set by setInitialShift() method. The default value is \( \sigma = 10^{-3} \). If the factorization fails, then the shift in doubled until it succeed or a maximum of ten attempts. If it still fails, as returned by the info() method, then you can either increase the initial shift, or better use another preconditioning technique.
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typedef SparseMatrix<Scalar,ColMajor,StorageIndex> Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::FactorType |
typedef _OrderingType Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::OrderingType |
typedef OrderingType::PermutationType Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::PermutationType |
typedef NumTraits<Scalar>::Real Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::RealScalar |
typedef PermutationType::StorageIndex Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::StorageIndex |
typedef Matrix<StorageIndex,Dynamic, 1> Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::VectorIx |
typedef std::vector<std::list<StorageIndex> > Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::VectorList |
typedef Matrix<RealScalar,Dynamic,1> Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::VectorRx |
typedef Matrix<Scalar,Dynamic,1> Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::VectorSx |
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Default constructor leaving the object in a partly non-initialized stage.
You must call compute() or the pair analyzePattern()/factorize() to make it valid.
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Constructor computing the incomplete factorization for the given matrix matrix.
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Computes the fill reducing permutation vector using the sparsity pattern of mat.
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Computes or re-computes the incomplete Cholesky factorization of the input matrix mat.
It is a shortcut for a sequential call to the analyzePattern() and factorize() methods.
void Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::factorize | ( | const _MatrixType & | mat | ) |
void Eigen::IncompleteCholesky< Scalar, _UpLo, _OrderingType >::factorize | ( | const MatrixType & | mat | ) |
Performs the numerical factorization of the input matrix mat.
The method analyzePattern() or compute() must have been called beforehand with a matrix having the same pattern.
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Reports whether previous computation was successful.
It triggers an assertion if *this
has not been initialized through the respective constructor, or a call to compute() or analyzePattern().
Success
if computation was successful, NumericalIssue
if the matrix appears to be negative.
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Set the initial shift parameter \( \sigma \).
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