| /external/eigen/Eigen/src/SVD/ |
| D | JacobiSVD.h | 76 void allocate(const JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd) in allocate() argument
78 if (svd.rows() != m_qr.rows() || svd.cols() != m_qr.cols()) in allocate()
81 ::new (&m_qr) QRType(svd.rows(), svd.cols()); in allocate()
83 if (svd.m_computeFullU) m_workspace.resize(svd.rows()); in allocate()
86 bool run(JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd, const MatrixType& matrix) in run() argument
91 …svd.m_workMatrix = m_qr.matrixQR().block(0,0,matrix.cols(),matrix.cols()).template triangularView<… in run()
92 if(svd.m_computeFullU) m_qr.matrixQ().evalTo(svd.m_matrixU, m_workspace); in run()
93 if(svd.computeV()) svd.m_matrixV = m_qr.colsPermutation(); in run()
122 void allocate(const JacobiSVD<MatrixType, FullPivHouseholderQRPreconditioner>& svd) in allocate() argument
124 if (svd.cols() != m_qr.rows() || svd.rows() != m_qr.cols()) in allocate()
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| /external/eigen/test/ |
| D | svd_common.h | 24 void svd_check_full(const MatrixType& m, const SvdType& svd) in svd_check_full() argument
41 sigma.diagonal() = svd.singularValues().template cast<Scalar>(); in svd_check_full()
42 MatrixUType u = svd.matrixU(); in svd_check_full()
43 MatrixVType v = svd.matrixV(); in svd_check_full()
69 SvdType svd(m, computationOptions); in svd_compare_to_full()
71 VERIFY_IS_APPROX(svd.singularValues(), referenceSvd.singularValues()); in svd_compare_to_full()
75 VERIFY( (svd.matrixV().adjoint()*svd.matrixV()).isIdentity(prec) ); in svd_compare_to_full()
76 …VERIFY_IS_APPROX( svd.matrixV().leftCols(diagSize) * svd.singularValues().asDiagonal() * svd.matri… in svd_compare_to_full()
82 VERIFY( (svd.matrixU().adjoint()*svd.matrixU()).isIdentity(prec) ); in svd_compare_to_full()
83 …VERIFY_IS_APPROX( svd.matrixU().leftCols(diagSize) * svd.singularValues().cwiseAbs2().asDiagonal()… in svd_compare_to_full()
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| D | qr_colpivoting.cpp | 57 JacobiSVD<MatrixType> svd(matrix, ComputeThinU | ComputeThinV); in cod() local
58 MatrixType svd_solution = svd.solve(rhs); in cod()
89 JacobiSVD<MatrixType> svd(matrix, ComputeFullU | ComputeFullV); in cod_fixedsize() local
90 Matrix<Scalar, Cols, Cols2> svd_solution = svd.solve(rhs); in cod_fixedsize()
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| /external/eigen/lapack/ |
| D | svd.cpp | 56 BDCSVD<PlainMatrixType> svd(mat,option);
58 make_vector(s,diag_size) = svd.singularValues().head(diag_size);
62 matrix(u,*m,*m,*ldu) = svd.matrixU();
63 matrix(vt,*n,*n,*ldvt) = svd.matrixV().adjoint();
67 matrix(u,*m,diag_size,*ldu) = svd.matrixU();
68 matrix(vt,diag_size,*n,*ldvt) = svd.matrixV().adjoint();
72 matrix(a,*m,*n,*lda) = svd.matrixU();
73 matrix(vt,*n,*n,*ldvt) = svd.matrixV().adjoint();
77 matrix(u,*m,*m,*ldu) = svd.matrixU();
78 matrix(a,diag_size,*n,*lda) = svd.matrixV().adjoint();
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| D | CMakeLists.txt | 171 add_lapack_test(ssvd.out svd.in xeigtsts)
238 add_lapack_test(dsvd.out svd.in xeigtstd)
303 add_lapack_test(csvd.out svd.in xeigtstc)
370 add_lapack_test(zsvd.out svd.in xeigtstz)
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| /external/eigen/doc/snippets/ |
| D | JacobiSVD_basic.cpp | 3 JacobiSVD<MatrixXf> svd(m, ComputeThinU | ComputeThinV); variable
4 cout << "Its singular values are:" << endl << svd.singularValues() << endl;
5 cout << "Its left singular vectors are the columns of the thin U matrix:" << endl << svd.matrixU() …
6 cout << "Its right singular vectors are the columns of the thin V matrix:" << endl << svd.matrixV()…
9 cout << "A least-squares solution of m*x = rhs is:" << endl << svd.solve(rhs) << endl;
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| /external/eigen/Eigen/src/Geometry/ |
| D | Umeyama.h | 131 JacobiSVD<MatrixType> svd(sigma, ComputeFullU | ComputeFullV);
139 if ( svd.matrixU().determinant() * svd.matrixV().determinant() < 0 )
143 Rt.block(0,0,m,m).noalias() = svd.matrixU() * S.asDiagonal() * svd.matrixV().transpose();
148 const Scalar c = Scalar(1)/src_var * svd.singularValues().dot(S);
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| D | Transform.h | 1081 JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
1083 Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
1084 VectorType sv(svd.singularValues());
1086 if(scaling) scaling->lazyAssign(svd.matrixV() * sv.asDiagonal() * svd.matrixV().adjoint());
1089 LinearMatrixType m(svd.matrixU());
1091 rotation->lazyAssign(m * svd.matrixV().adjoint());
1110 JacobiSVD<LinearMatrixType> svd(linear(), ComputeFullU | ComputeFullV);
1112 Scalar x = (svd.matrixU() * svd.matrixV().adjoint()).determinant(); // so x has absolute value 1
1113 VectorType sv(svd.singularValues());
1115 if(scaling) scaling->lazyAssign(svd.matrixU() * sv.asDiagonal() * svd.matrixU().adjoint());
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| D | Hyperplane.h | 109 JacobiSVD<Matrix<Scalar,2,3> > svd(m, ComputeFullV); in Through()
110 result.normal() = svd.matrixV().col(2); in Through()
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| D | Quaternion.h | 596 JacobiSVD<Matrix<Scalar,2,3> > svd(m, ComputeFullV);
597 Vector3 axis = svd.matrixV().col(2);
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| /external/eigen/doc/ |
| D | UsingBlasLapackBackends.dox | 104 JacobiSVD<MatrixXd> svd;
105 svd.compute(m1, ComputeThinV);
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| D | AsciiQuickReference.txt | 202 x = A.svd() .solve(b)); // Stable, slowest. #include <Eigen/SVD>
207 // .svd() -> .matrixU(), .singularValues(), and .matrixV()
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