#include <SimplicialCholesky.h>
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| void | compute (const MatrixType &matrix) |
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template<typename _MatrixType, int _UpLo>
class Eigen::SimplicialCholesky< _MatrixType, _UpLo >
- See also
- class SimplicialLDLT, class SimplicialLLT
◆ analyzePattern()
template<typename _MatrixType, int _UpLo>
| void analyzePattern |
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const MatrixType & | a | ) |
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inline |
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
- factorize()
◆ compute() [1/2]
template<typename _MatrixType, int _UpLo>
Computes the sparse Cholesky decomposition of matrix
References compute().
Referenced by compute().
◆ compute() [2/2]
| void compute |
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const MatrixType & | matrix | ) |
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inlineprotectedinherited |
Computes the sparse Cholesky decomposition of matrix
◆ factorize()
template<typename _MatrixType, int _UpLo>
| void factorize |
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const MatrixType & | a | ) |
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inline |
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
- analyzePattern()
References factorize().
Referenced by factorize().
◆ info()
Reports whether previous computation was successful.
- Returns
Success if computation was succesful, NumericalIssue if the matrix.appears to be negative.
◆ permutationP()
◆ permutationPinv()
◆ setShift()
| SimplicialCholesky< _MatrixType, _UpLo > & setShift |
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const RealScalar & | offset, |
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const RealScalar & | scale = 1 ) |
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inlineinherited |
Sets the shift parameters that will be used to adjust the diagonal coefficients during the numerical factorization.
During the numerical factorization, the diagonal coefficients are transformed by the following linear model:
d_ii = offset + scale * d_ii
The default is the identity transformation with offset=0, and scale=1.
- Returns
- a reference to
*this.
◆ solve() [1/2]
- Returns
- the solution x of
using the current decomposition of A.
- See also
- compute()
◆ solve() [2/2]
- Returns
- the solution x of
using the current decomposition of A.
- See also
- compute()
The documentation for this class was generated from the following file: