/external/opencv/cv/src/ |
H A D | cvshapedescr.cpp | 788 double eigenvalues[6], eigenvectors[36]; local 797 CvMat _EIGVECS = cvMat(6,6,CV_64F,eigenvectors), _EIGVALS = cvMat(6,1,CV_64F,eigenvalues); 855 double a = eigenvalues[i]; 873 // and find its eigenvalues and vectors too 878 if( eigenvalues[i] > 0 ) 881 if( i >= 3 /*eigenvalues[0] < DBL_EPSILON*/ ) 959 _EIGVALS = cvMat( 1, 2, CV_64F, eigenvalues ); 963 box->size.width = (float)(2./sqrt(eigenvalues[0])); 964 box->size.height = (float)(2./sqrt(eigenvalues[1]));
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/external/eigen/Eigen/src/Core/ |
H A D | MatrixBase.h | 125 /** \internal Return type of eigenvalues() */ 380 EigenvaluesReturnType eigenvalues() const;
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H A D | SelfAdjointView.h | 159 /** Return type of eigenvalues() */ 162 EigenvaluesReturnType eigenvalues() const;
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/external/eigen/Eigen/src/Eigen2Support/ |
H A D | LeastSquares.h | 161 *soundness = eig.eigenvalues().coeff(0)/eig.eigenvalues().coeff(1);
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/external/eigen/Eigen/src/Eigenvalues/ |
H A D | ComplexEigenSolver.h | 24 * \brief Computes eigenvalues and eigenvectors of general complex matrices 30 * The eigenvalues and eigenvectors of a matrix \f$ A \f$ are scalars 32 * \f$. If \f$ D \f$ is a diagonal matrix with the eigenvalues on 39 * eigenvalues and eigenvectors of a given function. The 73 /** \brief Type for vector of eigenvalues as returned by eigenvalues(). 120 * eigenvalues are computed; if false, only the eigenvalues are 148 * \f$ as returned by eigenvalues(). The eigenvectors are normalized to 159 eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues 181 const EigenvalueType& eigenvalues() const function in class:Eigen::ComplexEigenSolver [all...] |
H A D | EigenSolver.h | 23 * \brief Computes eigenvalues and eigenvectors of general matrices 29 * The eigenvalues and eigenvectors of a matrix \f$ A \f$ are scalars 31 * \f$ D \f$ is a diagonal matrix with the eigenvalues on the diagonal, and 36 * The eigenvalues and eigenvectors of a matrix may be complex, even when the 46 * Call the function compute() to compute the eigenvalues and eigenvectors of 49 * eigenvalues and eigenvectors at construction time. Once the eigenvalue and 50 * eigenvectors are computed, they can be retrieved with the eigenvalues() and 62 * \sa MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver 92 /** \brief Type for vector of eigenvalues as returned by eigenvalues() 243 const EigenvalueType& eigenvalues() const function in class:Eigen::EigenSolver [all...] |
H A D | GeneralizedEigenSolver.h | 23 * \brief Computes the generalized eigenvalues and eigenvectors of a pair of general matrices 29 * The generalized eigenvalues and eigenvectors of a matrix pair \f$ A \f$ and \f$ B \f$ are scalars 31 * \f$ D \f$ is a diagonal matrix with the eigenvalues on the diagonal, and 36 * The generalized eigenvalues and eigenvectors of a matrix pair may be complex, even when the 38 * singular. To workaround this difficulty, the eigenvalues are provided as a pair of complex \f$ \alpha \f$ 44 * Call the function compute() to compute the generalized eigenvalues and eigenvectors of 47 * eigenvalues and eigenvectors at construction time. Once the eigenvalue and 48 * eigenvectors are computed, they can be retrieved with the eigenvalues() and 55 * \sa MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver 85 /** \brief Type for vector of real scalar values eigenvalues a 198 EigenvalueType eigenvalues() const function in class:Eigen::GeneralizedEigenSolver [all...] |
H A D | MatrixBaseEigenvalues.h | 27 return ComplexEigenSolver<PlainObject>(m_eval, false).eigenvalues(); 39 return EigenSolver<PlainObject>(m_eval, false).eigenvalues(); 45 /** \brief Computes the eigenvalues of a matrix 46 * \returns Column vector containing the eigenvalues. 49 * This function computes the eigenvalues with the help of the EigenSolver 53 * The eigenvalues are repeated according to their algebraic multiplicity, 54 * so there are as many eigenvalues as rows in the matrix. 62 * \sa EigenSolver::eigenvalues(), ComplexEigenSolver::eigenvalues(), 63 * SelfAdjointView::eigenvalues() 67 MatrixBase<Derived>::eigenvalues() const function in class:Eigen::MatrixBase 89 SelfAdjointView<MatrixType, UpLo>::eigenvalues() const function in class:Eigen::SelfAdjointView [all...] |
H A D | SelfAdjointEigenSolver.h | 30 * \brief Computes eigenvalues and eigenvectors of selfadjoint matrices 38 * transpose. This class computes the eigenvalues and eigenvectors of a 40 * \f$ v \f$ such that \f$ Av = \lambda v \f$. The eigenvalues of a 42 * the eigenvalues on the diagonal, and \f$ V \f$ is a matrix with the 53 * Call the function compute() to compute the eigenvalues and eigenvectors of 56 * the eigenvalues and eigenvectors at construction time. Once the eigenvalue 57 * and eigenvectors are computed, they can be retrieved with the eigenvalues() 66 * \sa MatrixBase::eigenvalues(), class EigenSolver, class ComplexEigenSolver 94 /** \brief Type for vector of eigenvalues as returned by eigenvalues() 250 const RealVectorType& eigenvalues() const function in class:Eigen::SelfAdjointEigenSolver [all...] |
/external/eigen/bench/ |
H A D | eig33.cpp | 56 // eigenvalues are the roots to this equation, all guaranteed to be 75 // Compute the eigenvalues by solving for the roots of the polynomial. 106 // Compute the eigenvalues 111 // **here we assume 3 differents eigenvalues** 191 std::cerr << (evals - eig.eigenvalues()).transpose() << "\n";
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/external/eigen/doc/examples/ |
H A D | TutorialLinAlgSelfAdjointEigenSolver.cpp | 14 cout << "The eigenvalues of A are:\n" << eigensolver.eigenvalues() << endl; 16 << "corresponding to these eigenvalues:\n"
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/external/eigen/doc/snippets/ |
H A D | ComplexEigenSolver_compute.cpp | 6 cout << "The eigenvalues of A are:" << endl << ces.eigenvalues() << endl; 9 complex<float> lambda = ces.eigenvalues()[0]; 16 << ces.eigenvectors() * ces.eigenvalues().asDiagonal() * ces.eigenvectors().inverse() << endl;
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H A D | ComplexEigenSolver_eigenvalues.cpp | 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" 4 << endl << ces.eigenvalues() << endl;
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H A D | EigenSolver_EigenSolver_MatrixType.cpp | 5 cout << "The eigenvalues of A are:" << endl << es.eigenvalues() << endl; 8 complex<double> lambda = es.eigenvalues()[0]; 14 MatrixXcd D = es.eigenvalues().asDiagonal();
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H A D | EigenSolver_compute.cpp | 4 cout << "The eigenvalues of A are: " << es.eigenvalues().transpose() << endl; 5 es.compute(A + MatrixXf::Identity(4,4), false); // re-use es to compute eigenvalues of A+I 6 cout << "The eigenvalues of A+I are: " << es.eigenvalues().transpose() << endl;
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H A D | EigenSolver_eigenvalues.cpp | 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" 4 << endl << es.eigenvalues() << endl;
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H A D | GeneralizedEigenSolver.cpp | 5 cout << "The (complex) numerators of the generalzied eigenvalues are: " << ges.alphas().transpose() << endl; 6 cout << "The (real) denominatore of the generalzied eigenvalues are: " << ges.betas().transpose() << endl; 7 cout << "The (complex) generalzied eigenvalues are (alphas./beta): " << ges.eigenvalues().transpose() << endl;
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H A D | MatrixBase_eigenvalues.cpp | 2 VectorXcd eivals = ones.eigenvalues(); 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" << endl << eivals << endl;
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H A D | SelfAdjointEigenSolver_SelfAdjointEigenSolver.cpp | 5 cout << "The eigenvalues of A are: " << es.eigenvalues().transpose() << endl; 6 es.compute(A + Matrix4f::Identity(4,4)); // re-use es to compute eigenvalues of A+I 7 cout << "The eigenvalues of A+I are: " << es.eigenvalues().transpose() << endl;
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H A D | SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType.cpp | 6 cout << "The eigenvalues of A are:" << endl << es.eigenvalues() << endl; 9 double lambda = es.eigenvalues()[0]; 15 MatrixXd D = es.eigenvalues().asDiagonal();
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H A D | SelfAdjointEigenSolver_SelfAdjointEigenSolver_MatrixType2.cpp | 9 cout << "The eigenvalues of the pencil (A,B) are:" << endl << es.eigenvalues() << endl; 12 double lambda = es.eigenvalues()[0];
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H A D | SelfAdjointEigenSolver_compute_MatrixType.cpp | 5 cout << "The eigenvalues of A are: " << es.eigenvalues().transpose() << endl; 6 es.compute(A + MatrixXf::Identity(4,4)); // re-use es to compute eigenvalues of A+I 7 cout << "The eigenvalues of A+I are: " << es.eigenvalues().transpose() << endl;
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H A D | SelfAdjointEigenSolver_compute_MatrixType2.cpp | 7 cout << "The eigenvalues of the pencil (A,B) are:" << endl << es.eigenvalues() << endl; 9 cout << "The eigenvalues of the pencil (B,A) are:" << endl << es.eigenvalues() << endl;
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H A D | SelfAdjointEigenSolver_eigenvalues.cpp | 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" 4 << endl << es.eigenvalues() << endl;
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H A D | SelfAdjointView_eigenvalues.cpp | 2 VectorXd eivals = ones.selfadjointView<Lower>().eigenvalues(); 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" << endl << eivals << endl;
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