/external/eigen/doc/snippets/ |
ComplexEigenSolver_eigenvalues.cpp | 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" 4 << endl << ces.eigenvalues() << endl;
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EigenSolver_eigenvalues.cpp | 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" 4 << endl << es.eigenvalues() << endl;
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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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SelfAdjointEigenSolver_eigenvalues.cpp | 3 cout << "The eigenvalues of the 3x3 matrix of ones are:" 4 << endl << es.eigenvalues() << endl;
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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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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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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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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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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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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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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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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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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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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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/external/eigen/Eigen/src/Eigenvalues/ |
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...] |
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 149 * \f$ as returned by eigenvalues(). The eigenvectors are normalized to 160 eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.") 182 const EigenvalueType& eigenvalues() const function in class:Eigen::ComplexEigenSolver [all...] |
/external/eigen/test/ |
eigensolver_selfadjoint.cpp | 14 #include <Eigen/Eigenvalues> 31 VERIFY(eiSymm.eigenvalues().cwiseAbs().maxCoeff() <= (std::numeric_limits<RealScalar>::min)()); 36 (eiSymm.eigenvectors() * eiSymm.eigenvalues().asDiagonal())/scaling); 38 VERIFY_IS_APPROX(m.template selfadjointView<Lower>().eigenvalues(), eiSymm.eigenvalues()); 46 if(! eiSymm.eigenvalues().isApprox(eiDirect.eigenvalues(), eival_eps) ) 48 std::cerr << "reference eigenvalues: " << eiSymm.eigenvalues().transpose() << "\n" 49 << "obtained eigenvalues: " << eiDirect.eigenvalues().transpose() << "\n [all...] |
eigensolver_generic.cpp | 13 #include <Eigen/Eigenvalues> 37 (ei0.pseudoEigenvectors().template cast<Complex>()) * (ei0.eigenvalues().asDiagonal())); 43 ei1.eigenvectors() * ei1.eigenvalues().asDiagonal()); 45 VERIFY_IS_APPROX(a.eigenvalues(), ei1.eigenvalues()); 51 VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues()); 60 VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues()); 85 VERIFY_IS_MUCH_SMALLER_THAN(ei3.eigenvalues().norm(),RealScalar(1)) [all...] |
eigensolver_complex.cpp | 13 #include <Eigen/Eigenvalues> 89 VERIFY_IS_APPROX(symmA * ei0.eigenvectors(), ei0.eigenvectors() * ei0.eigenvalues().asDiagonal()); 93 VERIFY_IS_APPROX(a * ei1.eigenvectors(), ei1.eigenvectors() * ei1.eigenvalues().asDiagonal()); 94 // Note: If MatrixType is real then a.eigenvalues() uses EigenSolver and thus 96 verify_is_approx_upto_permutation(a.eigenvalues(), ei1.eigenvalues()); 102 VERIFY_IS_EQUAL(ei2.eigenvalues(), ei1.eigenvalues()); 111 VERIFY_IS_APPROX(ei1.eigenvalues(), eiNoEivecs.eigenvalues()); [all...] |
eigensolver_generalized_real.cpp | 13 #include <Eigen/Eigenvalues> 41 VERIFY_IS_EQUAL(eig.eigenvalues().imag().cwiseAbs().maxCoeff(), 0); 43 VectorType realEigenvalues = eig.eigenvalues().real(); 45 VERIFY_IS_APPROX(realEigenvalues, symmEig.eigenvalues()); 48 typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType D = eig.eigenvalues().asDiagonal(); 68 typename GeneralizedEigenSolver<MatrixType>::EigenvectorsType D = eig.eigenvalues().asDiagonal();
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/external/eigen/doc/examples/ |
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/lapack/ |
eigenvalues.cpp | 11 #include <Eigen/Eigenvalues> 57 make_vector(w,*n) = eig.eigenvalues();
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/external/eigen/unsupported/test/ |
mpreal_support.cpp | 4 #include <Eigen/Eigenvalues> 53 // symmetric eigenvalues 56 VERIFY( (S.selfadjointView<Lower>() * eig.eigenvectors()).isApprox(eig.eigenvectors() * eig.eigenvalues().asDiagonal(), NumTraits<mpreal>::dummy_precision()*1e3) );
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forward_adolc.cpp | 139 A.selfadjointView<Lower>().eigenvalues();
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/external/opencv/cv/src/ |
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])); [all...] |