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  /external/eigen/doc/snippets/
JacobiSVD_basic.cpp 6 cout << "Its right singular vectors are the columns of the thin V matrix:" << endl << svd.matrixV() << endl;
  /external/eigen/test/
jacobisvd.cpp 39 MatrixVType v = svd.matrixV();
64 VERIFY_IS_APPROX(svd.matrixV(), referenceSvd.matrixV());
66 VERIFY_IS_APPROX(svd.matrixV(), referenceSvd.matrixV().leftCols(diagSize));
124 VERIFY_IS_APPROX(m, svd.matrixU().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matrixV().leftCols(diagSize).adjoint());
158 VERIFY_RAISES_ASSERT(svd.matrixV())
165 VERIFY_RAISES_ASSERT(svd.matrixV())
173 VERIFY_RAISES_ASSERT(svd.matrixV())
177 svd.matrixV();
    [all...]
  /external/eigen/Eigen/src/Geometry/
Umeyama.h 145 if ( svd.matrixU().determinant() * svd.matrixV().determinant() > 0 ) {
146 Rt.block(0,0,m,m).noalias() = svd.matrixU()*svd.matrixV().transpose();
149 Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
153 Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
Transform.h     [all...]
Quaternion.h 601 Vector3 axis = svd.matrixV().col(2);
  /external/eigen/test/eigen2/
eigen2_svd.cpp 38 VERIFY_IS_APPROX(a, matU * sigma * svd.matrixV().transpose());
  /external/eigen/Eigen/src/Eigen2Support/Geometry/
Transform.h 622 Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
627 scaling->noalias() = svd.matrixV() * sv.asDiagonal() * svd.matrixV().adjoint();
633 rotation->noalias() = m * svd.matrixV().adjoint();
653 Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
664 rotation->noalias() = m * svd.matrixV().adjoint();
  /external/ceres-solver/internal/ceres/
covariance_impl.cc 824 svd.matrixV() *
826 svd.matrixV().transpose();
  /external/eigen/Eigen/src/SVD/
JacobiSVD.h 604 const MatrixVType& matrixV() const
    [all...]
  /external/eigen/Eigen/src/Eigen2Support/
SVD.h 66 const MatrixVType& matrixV() const { return m_matV; }

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