| /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 | |
