Eigen::SimplicialCholesky
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void |
analyzePattern (const MatrixType &a) |
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SimplicialCholesky & |
compute (const MatrixType &matrix) |
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void |
factorize (const MatrixType &a) |
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Public Member Functions inherited from Eigen::SimplicialCholeskyBase< SimplicialCholesky< _MatrixType, _UpLo, _Ordering > >
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ComputationInfo |
info () const |
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Reports whether previous computation was successful. More...
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const PermutationMatrix< Dynamic, Dynamic, StorageIndex > & |
permutationP () const |
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const PermutationMatrix< Dynamic, Dynamic, StorageIndex > & |
permutationPinv () const |
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SimplicialCholesky< _MatrixType, _UpLo, _Ordering > & |
setShift (const RealScalar &offset, const RealScalar &scale=1) |
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SimplicialCholeskyBase () |
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Public Member Functions inherited from Eigen::SparseSolverBase< SimplicialCholesky< _MatrixType, _UpLo, _Ordering > >
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const Solve< SimplicialCholesky< _MatrixType, _UpLo, _Ordering >, Rhs > |
solve (const MatrixBase< Rhs > &b) const |
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const Solve< SimplicialCholesky< _MatrixType, _UpLo, _Ordering >, Rhs > |
solve (const SparseMatrixBase< Rhs > &b) const |
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SparseSolverBase () |
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analyzePattern()
template<typename _MatrixType , int _UpLo, typename _Ordering >
Performs a symbolic decomposition on the sparcity of matrix.
This function is particularly useful when solving for several problems having the same structure.
- See also
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factorize()
compute()
template<typename _MatrixType , int _UpLo, typename _Ordering >
Computes the sparse Cholesky decomposition of matrix
factorize()
template<typename _MatrixType , int _UpLo, typename _Ordering >
Performs a numeric decomposition of matrix
The given matrix must has the same sparcity than the matrix on which the symbolic decomposition has been performed.
- See also
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analyzePattern()
The documentation for this class was generated from the following file: