| /external/eigen/Eigen/src/Cholesky/ |
| D | LLT.h | 50 template<typename _MatrixType, int _UpLo> class LLT
78 LLT() : m_matrix(), m_isInitialized(false) {} in LLT() function
86 LLT(Index size) : m_matrix(size, size), in LLT() function
89 LLT(const MatrixType& matrix) in LLT() function
121 inline const internal::solve_retval<LLT, Rhs>
127 return internal::solve_retval<LLT, Rhs>(*this, b.derived()); in solve()
144 LLT& compute(const MatrixType& matrix);
174 LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1);
391 LLT<MatrixType,_UpLo>& LLT<MatrixType,_UpLo>::compute(const MatrixType& a)
414 LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& si…
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| /external/eigen/Eigen/ |
| D | OrderingMethods | 15 * the sparse matrix decomposition (LLT, LU, QR).
19 * the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A).
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| D | Cholesky | 23 #include "src/Cholesky/LLT.h"
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| D | CholmodSupport | 17 * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization.
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| /external/eigen/test/ |
| D | nomalloc.cpp | 130 Eigen::LLT<Matrix> LLT; LLT.compute(A); in ctms_decompositions() local
131 X = LLT.solve(B); in ctms_decompositions()
132 x = LLT.solve(b); in ctms_decompositions()
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| D | cholesky.cpp | 94 LLT<SquareMatrixType,Lower> chollo(symmLo); in cholesky()
102 LLT<SquareMatrixType,Upper> cholup(symmUp); in cholesky()
237 CALL_SUBTEST(( test_chol_update<SquareMatrixType,LLT>(symm) )); in cholesky()
272 LLT<RealMatrixType,Lower> chollo(symmLo); in cholesky_cplx()
361 LLT<MatrixType> llt; in cholesky_verify_assert()
399 CALL_SUBTEST_9( LLT<MatrixXf>(10) ); in test_cholesky()
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| /external/eigen/test/eigen2/ |
| D | eigen2_cholesky.cpp | 80 LLT<SquareMatrixType> chol(symm); in cholesky()
94 LLT<SquareMatrixType> chol(symm); in cholesky()
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| /external/eigen/failtest/ |
| D | llt_int.cpp | 13 LLT<Matrix<SCALAR,Dynamic,Dynamic> > llt(Matrix<SCALAR,Dynamic,Dynamic>::Random(10,10)); in main()
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| /external/eigen/doc/snippets/ |
| D | LLT_example.cpp | 5 LLT<MatrixXd> lltOfA(A); // compute the Cholesky decomposition of A
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| /external/eigen/doc/examples/ |
| D | TutorialLinAlgComputeTwice.cpp | 10 LLT<Matrix2f> llt; in main()
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| /external/ceres-solver/internal/ceres/ |
| D | dense_normal_cholesky_solver.cc | 99 Eigen::LLT<Matrix, Eigen::Upper> llt = in SolveUsingEigen()
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| D | schur_complement_solver.cc | 137 Eigen::LLT<Matrix, Eigen::Upper> llt = in SolveReducedLinearSystem()
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| /external/eigen/Eigen/src/Eigenvalues/ |
| D | GeneralizedSelfAdjointEigenSolver.h | 176 LLT<MatrixType> cholB(matB); in compute()
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| /external/eigen/bench/spbench/ |
| D | spbench.dtd | 4 <!ELEMENT TYPE (#PCDATA)> <!-- One of LU, LLT, LDLT, ITER -->
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| /external/eigen/bench/ |
| D | benchCholesky.cpp | 70 LLT<SquareMatrixType> chol(covMat); in benchLLT()
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| D | sparse_cholesky.cpp | 113 LLT<DenseMatrix> chol(m1); in main()
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| /external/eigen/doc/ |
| D | SparseLinearSystems.dox | 108 In the compute() function, the matrix is generally factorized: LLT for self-adjoint matrices, LDLT …
147 …LDLT <TH> CHOLMOD LDLT <TH > PASTIX LDLT <TH > LLT <TH > CHOLMOD SP LLT <TH > CHOLMOD LLT <TH > PA…
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| D | TopicAliasing.dox | 121 <tr class="alt"> <td> LLT::solve() </td> <td> LLT::solveInPlace() </td> </tr>
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| D | TopicLinearAlgebraDecompositions.dox | 90 <td>LLT</td>
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| D | TutorialLinearAlgebra.dox | 83 <td>LLT</td>
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| D | TutorialSparse.dox | 12 …/td><td>\code#include <Eigen/SparseCholesky>\endcode</td><td>Direct sparse LLT and LDLT Cholesky f…
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| D | QuickReference.dox | 19 …e Cholesky \endlink</td><td>\code#include <Eigen/Cholesky>\endcode</td><td>LLT and LDLT Cholesky f…
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| /external/eigen/Eigen/src/Core/ |
| D | SelfAdjointView.h | 152 const LLT<PlainObject, UpLo> llt() const;
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| D | MatrixBase.h | 361 const LLT<PlainObject> llt() const;
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| /external/eigen/Eigen/src/Core/util/ |
| D | ForwardDeclarations.h | 225 template<typename MatrixType, int UpLo = Lower> class LLT;
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