The base class for the direct Cholesky factorization of Cholmod.
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#include <CholmodSupport.h>
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enum | { UpLo = _UpLo
} |
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enum | { ColsAtCompileTime = MatrixType::ColsAtCompileTime,
MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
} |
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typedef _MatrixType | MatrixType |
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typedef MatrixType::Scalar | Scalar |
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typedef MatrixType::RealScalar | RealScalar |
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typedef MatrixType | CholMatrixType |
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typedef MatrixType::StorageIndex | StorageIndex |
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Derived & | derived () |
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const Derived & | derived () const |
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cholmod_common | m_cholmod |
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cholmod_factor * | m_cholmodFactor |
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double | m_shiftOffset [2] |
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ComputationInfo | m_info |
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int | m_factorizationIsOk |
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int | m_analysisIsOk |
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bool | m_isInitialized |
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bool | m_isInitialized |
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template<typename _MatrixType, int _UpLo, typename Derived>
class Eigen::CholmodBase< _MatrixType, _UpLo, Derived >
The base class for the direct Cholesky factorization of Cholmod.
- See also
- class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT
◆ analyzePattern()
template<typename _MatrixType , int _UpLo, typename Derived >
void Eigen::CholmodBase< _MatrixType, _UpLo, Derived >::analyzePattern |
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const MatrixType & |
matrix | ) |
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inline |
Performs a symbolic decomposition on the sparsity pattern of matrix.
This function is particularly useful when solving for several problems having the same structure.
- See also
- factorize()
◆ cholmod()
template<typename _MatrixType , int _UpLo, typename Derived >
Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations. See the Cholmod user guide for details.
◆ compute()
template<typename _MatrixType , int _UpLo, typename Derived >
Derived& Eigen::CholmodBase< _MatrixType, _UpLo, Derived >::compute |
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const MatrixType & |
matrix | ) |
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inline |
Computes the sparse Cholesky decomposition of matrix
◆ determinant()
template<typename _MatrixType , int _UpLo, typename Derived >
- Returns
- the determinant of the underlying matrix from the current factorization
◆ factorize()
template<typename _MatrixType , int _UpLo, typename Derived >
void Eigen::CholmodBase< _MatrixType, _UpLo, Derived >::factorize |
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const MatrixType & |
matrix | ) |
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inline |
Performs a numeric decomposition of matrix
The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been performed.
- See also
- analyzePattern()
◆ info()
template<typename _MatrixType , int _UpLo, typename Derived >
Reports whether previous computation was successful.
- Returns
Success
if computation was successful, NumericalIssue
if the matrix.appears to be negative.
◆ logDeterminant()
template<typename _MatrixType , int _UpLo, typename Derived >
- Returns
- the log determinant of the underlying matrix from the current factorization
◆ setShift()
template<typename _MatrixType , int _UpLo, typename Derived >
Derived& Eigen::CholmodBase< _MatrixType, _UpLo, Derived >::setShift |
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const RealScalar & |
offset | ) |
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inline |
Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization.
During the numerical factorization, an offset term is added to the diagonal coefficients:
d_ii
= offset + d_ii
The default is offset=0.
- Returns
- a reference to
*this
.
The documentation for this class was generated from the following file: