/external/eigen/test/ |
D | cholesky.cpp | 77 MatrixType matB = MatrixType::Random(rows,cols), matX(rows,cols); in cholesky() local 98 matX = chollo.solve(matB); in cholesky() 99 VERIFY_IS_APPROX(symm * matX, matB); in cholesky() 106 matX = cholup.solve(matB); in cholesky() 107 VERIFY_IS_APPROX(symm * matX, matB); in cholesky() 135 matX = ldltlo.solve(matB); in cholesky() 136 VERIFY_IS_APPROX(symm * matX, matB); in cholesky() 142 matX = ldltup.solve(matB); in cholesky() 143 VERIFY_IS_APPROX(symm * matX, matB); in cholesky() 155 matX = matB; in cholesky() [all …]
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D | sparse_solvers.cpp | 80 SparseMatrix<Scalar> matB(rows, rows); in sparse_solvers() local 85 initSparse<Scalar>(density, refMatB, matB); in sparse_solvers() 87 m2.template triangularView<Lower>().solveInPlace(matB); in sparse_solvers() 88 VERIFY_IS_APPROX(matB.toDense(), refMatB); in sparse_solvers() 92 initSparse<Scalar>(density, refMatB, matB); in sparse_solvers() 94 m2.template triangularView<Upper>().solveInPlace(matB); in sparse_solvers() 95 VERIFY_IS_APPROX(matB, refMatB); in sparse_solvers()
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/external/eigen/doc/snippets/ |
D | TopicAliasing_mult2.cpp | 1 MatrixXf matA(2,2), matB(2,2); variable 5 matB = matA * matA; 6 cout << matB << endl << endl; 9 matB.noalias() = matA * matA; 10 cout << matB;
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D | Tutorial_AdvancedInitialization_Block.cpp | 3 MatrixXf matB(4, 4); variable 4 matB << matA, matA/10, matA/10, matA; 5 std::cout << matB << std::endl;
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/external/eigen/Eigen/src/Eigenvalues/ |
D | GeneralizedSelfAdjointEigenSolver.h | 107 GeneralizedSelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB, 111 compute(matA, matB, options); 154 GeneralizedSelfAdjointEigenSolver& compute(const MatrixType& matA, const MatrixType& matB, 164 compute(const MatrixType& matA, const MatrixType& matB, int options) in compute() argument 166 eigen_assert(matA.cols()==matA.rows() && matB.rows()==matA.rows() && matB.cols()==matB.rows()); in compute() 176 LLT<MatrixType> cholB(matB); in compute()
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D | SelfAdjointEigenSolver.h | 333 …SelfAdjointEigenSolver(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = … 339 …static_cast<GeneralizedSelfAdjointEigenSolver<MatrixType>*>(this)->compute(matA, matB, computeEige… 347 void compute(const MatrixType& matA, const MatrixType& matB, bool computeEigenvectors = true) 349 compute(matA, matB, computeEigenvectors ? ComputeEigenvectors : EigenvaluesOnly);
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/external/eigen/test/eigen2/ |
D | eigen2_cholesky.cpp | 34 MatrixType matB = MatrixType::Random(rows,cols), matX(rows,cols); in cholesky() local 75 ldlt.solve(matB, &matX); in cholesky() 76 VERIFY_IS_APPROX(symm * matX, matB); in cholesky() 85 chol.solve(matB, &matX); in cholesky() 86 VERIFY_IS_APPROX(symm * matX, matB); in cholesky()
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/external/skia/src/effects/ |
D | SkColorMatrix.cpp | 72 const SkColorMatrix& matB) { in setConcat() argument 76 if (&matA == this || &matB == this) { in setConcat() 81 const SkScalar* b = matB.fMat; in setConcat()
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/external/skia/legacy/src/utils/ |
D | SkColorMatrix.cpp | 71 const SkColorMatrix& matB) { in setConcat() argument 75 if (&matA == this || &matB == this) { in setConcat() 80 const SkScalar* b = matB.fMat; in setConcat()
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/external/eigen/doc/ |
D | I11_Aliasing.dox | 171 the same when the product is assigned to a different matrix (e.g., <tt>matB = matA * matA</tt>). In… 172 it is more efficient to evaluate the product directly into \c matB instead of evaluating it first i… 173 temporary matrix and copying that matrix to \c matB. 176 aliasing, as follows: <tt>matB.noalias() = matA * matA</tt>. This allows Eigen to evaluate the matr… 177 <tt>matA * matA</tt> directly into \c matB.
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/external/opencv/cvaux/src/ |
D | cvepilines.cpp | 2427 CvMat matB = cvMat( 8, 1, CV_64F, b ); in icvComputePerspectiveCoeffs() local 2431 CV_CALL( cvMatMulAdd( &matInvA, &matB, 0, &matX )); in icvComputePerspectiveCoeffs() 2567 CvMat matB = cvMat( 8, 1, CV_64F, b ); in cvInitPerspectiveTransform() local 2571 CV_CALL( cvMatMulAdd( &matInvA, &matB, 0, &matX )); in cvInitPerspectiveTransform()
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