Given a linear block matrix operator and appropriate boundary conditions, this class will produce an Eigen matrix representing the discretized version. The implementation will naturally involve column pivoting, and the pivot matrix is also stored.
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| Discretize () |
| Null Constructor. More...
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | operator() (const LinopMat< std::complex< T > > &Lmat_, const BcMat< std::complex< T > > &bc_) |
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | operator() (const LinopMat< std::complex< T > > &Lmat_) |
| Discretization based on a previous call with Boundary conditions. Then other LinopMats can be discretized based on a previous Lbc called with operator()(const LinopMat<T> &Lmat, const BcMat<T> &bc). More...
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | ChebDiff (const LinopMat< std::complex< T > > &Lmat_) |
| Chebyshev differentiation operator for LinopMat. More...
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | MatAppend (const LinopMat< std::complex< T > > &Lmat_, const BcMat< std::complex< T > > &bc_) |
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| MatGen () |
| Null Constructor. More...
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| MatGen (int n_) |
| Constructor. More...
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void | compute (int n_) |
| Call this to generate integration matrices for highest order n. More...
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void | clear () |
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | P |
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | subs_mat |
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | A1 |
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Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > | invmat_temp |
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std::vector< int > | highest_each_column |
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int | num_bc |
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std::vector< Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > > | mats |
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std::vector< Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > > | mats2 |
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std::vector< Eigen::Matrix< std::complex< T >, Eigen::Dynamic, Eigen::Dynamic > > | con_mats |
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template<class T>
class sis::Discretize< std::complex< T > >
Given a linear block matrix operator and appropriate boundary conditions, this class will produce an Eigen matrix representing the discretized version. The implementation will naturally involve column pivoting, and the pivot matrix is also stored.
Definition at line 9855 of file sis.hpp.