/external/eigen/unsupported/test/ |
mpreal_support.cpp | 4 #include <Eigen/Eigenvalues> 45 // symmetric eigenvalues 48 VERIFY( (S.selfadjointView<Lower>() * eig.eigenvectors()).isApprox(eig.eigenvectors() * eig.eigenvalues().asDiagonal(), NumTraits<mpreal>::dummy_precision()*1e3) );
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forward_adolc.cpp | 141 A.selfadjointView<Lower>().eigenvalues();
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matrix_function.cpp | 24 // Returns a matrix with eigenvalues clustered around 0, 1 and 2. 44 // Returns a matrix with eigenvalues clustered around 0 and +/- i. 115 RealScalar maxImagPartOfSpectrum = A.eigenvalues().imag().cwiseAbs().maxCoeff(); 121 // identity X.exp().log() = X only holds if Im(lambda) < pi for all eigenvalues of X
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/external/opencv3/samples/cpp/tutorial_code/ml/introduction_to_pca/ |
introduction_to_pca.cpp | 68 //Store the eigenvalues and eigenvectors 76 eigen_val[i] = pca_analysis.eigenvalues.at<double>(0, i);
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/external/ceres-solver/internal/ceres/ |
polynomial.cc | 48 // "Balancing a Matrix for Calculation of Eigenvalues and Eigenvectors". 232 // Find its (complex) eigenvalues. 235 LOG(ERROR) << "Failed to extract eigenvalues from companion matrix."; 241 *real = solver.eigenvalues().real(); 248 *imaginary = solver.eigenvalues().imag();
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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...] |
/external/eigen/Eigen/src/Eigenvalues/ |
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...] |
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 as returned by betas() 198 EigenvalueType eigenvalues() const function in class:Eigen::GeneralizedEigenSolver [all...] |
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...] |
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/ |
eig33.cpp | 41 #include <Eigen/Eigenvalues> 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/unsupported/Eigen/src/Polynomials/ |
PolynomialSolver.h | 322 * Currently a QR algorithm is used to compute the eigenvalues of the companion matrix of 351 m_roots = m_eigenSolver.eigenvalues();
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/external/eigen/Eigen/src/Core/ |
SelfAdjointView.h | 159 /** Return type of eigenvalues() */ 162 EigenvaluesReturnType eigenvalues() const;
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MatrixBase.h | 125 /** \internal Return type of eigenvalues() */ 374 EigenvaluesReturnType eigenvalues() const;
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/external/opencv3/modules/core/include/opencv2/ |
core.hpp | 159 face recognition). Eigenvalues of this "scrambled" matrix match the eigenvalues of the true 2368 Mat eigenvalues; \/\/!< eigenvalues of the covariation matrix member in class:cv::PCA 2434 Mat eigenvalues() const { return _eigenvalues; } function in class:cv::LDA [all...] |
/external/opencv3/modules/java/src/ |
core+Core.java | [all...] |
core.cpp | 3562 Mat& eigenvalues = *((Mat*)eigenvalues_nativeObj); local 3585 Mat& eigenvalues = *((Mat*)eigenvalues_nativeObj); local [all...] |
/external/opencv3/modules/calib3d/src/ |
dls.cpp | 11 # include <Eigen/Eigenvalues> 134 cv::Mat eigenvalues, eigenvectors; local 135 cv::eigen(H, eigenvalues, eigenvectors); 137 if(positive_eigenvalues(&eigenvalues)) 281 Eigen::MatrixXd eigval_real = ces.eigenvalues().real(); 282 Eigen::MatrixXd eigval_imag = ces.eigenvalues().imag(); 292 eigenval_real = es.eigenvalues(); [all...] |
dls.h | 72 bool positive_eigenvalues(const cv::Mat * eigenvalues); 95 // Holds the computed eigenvalues. 707 // Copy eigenvalues to OpenCV Matrix. 767 // Returns the eigenvalues of the Eigenvalue Decomposition. 768 Mat eigenvalues() { return _eigenvalues; } function in class:EigenvalueDecomposition
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/external/opencv3/modules/core/test/ |
test_mat.cpp | 351 // check pca eigenvalues 353 err = cvtest::norm( rPCA.eigenvalues, subEval, NORM_L2 ); 356 ts->printf( cvtest::TS::LOG, "pca.eigenvalues is incorrect (CV_PCA_DATA_AS_ROW); err = %f\n", err ); 527 err = cvtest::norm( rPCA.eigenvalues, lPCA.eigenvalues, CV_RELATIVE_L2 ); [all...] |
/external/eigen/unsupported/Eigen/src/Eigenvalues/ |
ArpackSelfAdjointEigenSolver.h | 57 /** \brief Type for vector of eigenvalues as returned by eigenvalues(). 79 /** \brief Constructor; computes generalized eigenvalues of given matrix with respect to another matrix. 81 * \param[in] A Self-adjoint matrix whose eigenvalues / eigenvectors will 85 * \param[in] nbrEigenvalues The number of eigenvalues / eigenvectors to compute. 89 * largest algebraic, or smallest algebraic eigenvalues. Alternatively, this 91 * eigenvalues closest to this value will be found. 93 * \param[in] tol What tolerance to find the eigenvalues to. Default is 0, which 97 * to compute the eigenvalues of the matrix \p A with respect to \p B. The eigenvectors are computed if 114 /** \brief Constructor; computes eigenvalues of given matrix 245 const Matrix<Scalar, Dynamic, 1>& eigenvalues() const function in class:Eigen::ArpackGeneralizedSelfAdjointEigenSolver [all...] |
/external/eigen/unsupported/Eigen/src/MatrixFunctions/ |
MatrixSquareRoot.h | 134 // pre: T.block(i,i,2,2) has complex conjugate eigenvalues 140 // TODO: This case (2-by-2 blocks with complex conjugate eigenvalues) is probably hidden somewhere 145 = (es.eigenvectors() * es.eigenvalues().cwiseSqrt().asDiagonal() * es.eigenvectors().inverse()).real();
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/external/opencv3/modules/core/src/ |
lda.cpp | 257 // Holds the computed eigenvalues. 869 // Copy eigenvalues to OpenCV Matrix. 929 // Returns the eigenvalues of the Eigenvalue Decomposition. 930 Mat eigenvalues() { return _eigenvalues; } function in class:cv::EigenvalueDecomposition [all...] |
matmul.cpp | [all...] |
/cts/apps/CtsVerifier/libs/ |
opencv3-android.jar | |