| /external/eigen/doc/snippets/ |
| SelfAdjointView_operatorNorm.cpp | 3 << ones.selfadjointView<Lower>().operatorNorm() << endl;
|
| SelfAdjointView_eigenvalues.cpp | 2 VectorXd eivals = ones.selfadjointView<Lower>().eigenvalues();
|
| /external/eigen/test/ |
| sparse_permutations.cpp | 35 up_sym_d = mat_d.template selfadjointView<Upper>();
36 lo_sym_d = mat_d.template selfadjointView<Lower>();
68 res = mat.template selfadjointView<Upper>().twistedBy(p_null);
72 res = mat.template selfadjointView<Lower>().twistedBy(p_null);
77 res = up.template selfadjointView<Upper>().twistedBy(p_null);
81 res = lo.template selfadjointView<Lower>().twistedBy(p_null);
86 res = mat.template selfadjointView<Upper>();
90 res = mat.template selfadjointView<Lower>();
94 res = up.template selfadjointView<Upper>();
98 res = lo.template selfadjointView<Lower>()
[all...] |
| eigensolver_selfadjoint.cpp | 49 VERIFY((symmA.template selfadjointView<Lower>() * eiSymm.eigenvectors()).isApprox(
51 VERIFY_IS_APPROX(symmA.template selfadjointView<Lower>().eigenvalues(), eiSymm.eigenvalues());
54 VERIFY((symmA.template selfadjointView<Lower>() * eiDirect.eigenvectors()).isApprox(
56 VERIFY_IS_APPROX(symmA.template selfadjointView<Lower>().eigenvalues(), eiDirect.eigenvalues());
65 VERIFY((symmA.template selfadjointView<Lower>() * eiSymmGen.eigenvectors()).isApprox(
66 symmB.template selfadjointView<Lower>() * (eiSymmGen.eigenvectors() * eiSymmGen.eigenvalues().asDiagonal()), largerEps));
71 VERIFY((symmB.template selfadjointView<Lower>() * (symmA.template selfadjointView<Lower>() * eiSymmGen.eigenvectors())).isApprox(
77 VERIFY((symmA.template selfadjointView<Lower>() * (symmB.template selfadjointView<Lower>() * eiSymmGen.eigenvectors())).isApprox
[all...] |
| product_symm.cpp | 39 m3 = m2.template selfadjointView<Lower>();
41 VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>() * (s2*rhs1),
45 m3 = m2.template selfadjointView<Upper>();
47 VERIFY_IS_APPROX(rhs12 += (s1*m2).template selfadjointView<Upper>() * (s2*rhs1),
51 VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Lower>() * (s2*rhs2.adjoint()),
55 VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<Upper>() * (s2*rhs2.adjoint()),
59 VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs2.adjoint()),
64 VERIFY_IS_APPROX(rhs12 -= (s1*m2).template selfadjointView<Lower>() * (s2*rhs3),
68 VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs3).conjugate(),
73 VERIFY_IS_APPROX(rhs12.noalias() += s1 * ((m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs3).conjugate())
[all...] |
| product_syrk.cpp | 36 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(rhs2,s1)._expression()),
40 VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs2,s1)._expression(),
44 VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs1.adjoint(),s1)._expression(),
48 VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs1.adjoint(),s1)._expression(),
52 VERIFY_IS_APPROX(m2.template selfadjointView<Lower>().rankUpdate(rhs3.adjoint(),s1)._expression(),
56 VERIFY_IS_APPROX(m2.template selfadjointView<Upper>().rankUpdate(rhs3.adjoint(),s1)._expression(),
60 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c),s1)._expression()),
64 VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c),s1)._expression()),
68 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(),s1)._expression()),
72 VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(),s1)._expression())
[all...] |
| selfadjoint.cpp | 12 // This file tests the basic selfadjointView API,
30 m3 = m1.template selfadjointView<Upper>();
35 m3 = m1.template selfadjointView<Lower>();
42 Matrix3d m = Matrix3d::Random().selfadjointView<Lower>();
|
| nomalloc.cpp | 74 m2.col(0).noalias() = m1.template selfadjointView<Upper>() * m1.col(0);
75 m2.col(0).noalias() -= m1.adjoint().template selfadjointView<Upper>() * m1.col(0);
76 m2.col(0).noalias() -= m1.template selfadjointView<Upper>() * m1.row(0).adjoint();
77 m2.col(0).noalias() -= m1.adjoint().template selfadjointView<Upper>() * m1.row(0).adjoint();
79 m2.row(0).noalias() = m1.row(0) * m1.template selfadjointView<Upper>();
80 m2.row(0).noalias() -= m1.row(0) * m1.adjoint().template selfadjointView<Upper>();
81 m2.row(0).noalias() -= m1.col(0).adjoint() * m1.template selfadjointView<Upper>();
82 m2.row(0).noalias() -= m1.col(0).adjoint() * m1.adjoint().template selfadjointView<Upper>();
85 m2.template selfadjointView<Lower>().rankUpdate(m1.col(0),-1);
86 m2.template selfadjointView<Lower>().rankUpdate(m1.row(0),-1)
[all...] |
| product_notemporary.cpp | 87 VERIFY_EVALUATION_COUNT( m3.noalias() -= (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2*s3).adjoint(), 0);
88 VERIFY_EVALUATION_COUNT( m3.noalias() = s2 * m2.adjoint() * (s1 * m1.adjoint()).template selfadjointView<Upper>(), 0);
89 VERIFY_EVALUATION_COUNT( rm3.noalias() = (s1 * m1.adjoint()).template selfadjointView<Lower>() * m2.adjoint(), 0);
92 VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() = (s1 * m1).adjoint().template selfadjointView<Lower>() * (-m2.row(c0)*s3).adjoint(), 1);
93 VERIFY_EVALUATION_COUNT( m3.col(c0).noalias() -= (s1 * m1).adjoint().template selfadjointView<Upper>() * (-m2.row(c0)*s3).adjoint(), 1);
95 VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() += m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * (s1*m2.block(r0,c0,r1,c1)), 0);
96 VERIFY_EVALUATION_COUNT( m3.block(r0,c0,r1,c1).noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Upper>() * m2.block(r0,c0,r1,c1), 0);
98 VERIFY_EVALUATION_COUNT( m3.template selfadjointView<Lower>().rankUpdate(m2.adjoint()), 0);
102 VERIFY_EVALUATION_COUNT( m3.noalias() = m1.block(r0,r0,r1,r1).template selfadjointView<Lower>() * m2.block(r0,c0,r1,c1), 1);
|
| product_selfadjoint.cpp | 43 m2.template selfadjointView<Lower>().rankUpdate(v1,v2);
47 m2.template selfadjointView<Upper>().rankUpdate(-v1,s2*v2,s3);
51 m2.template selfadjointView<Upper>().rankUpdate(-s2*r1.adjoint(),r2.adjoint()*s3,s1);
57 m2.block(1,1,rows-1,cols-1).template selfadjointView<Lower>().rankUpdate(v1.tail(rows-1),v2.head(cols-1));
|
| cholesky.cpp | 173 m2 += symmLo.template selfadjointView<Lower>().llt().solve(matB);
174 VERIFY_IS_APPROX(m2, m1 + symmLo.template selfadjointView<Lower>().llt().solve(matB));
176 m2 -= symmLo.template selfadjointView<Lower>().llt().solve(matB);
177 VERIFY_IS_APPROX(m2, m1 - symmLo.template selfadjointView<Lower>().llt().solve(matB));
179 m2.noalias() += symmLo.template selfadjointView<Lower>().llt().solve(matB);
180 VERIFY_IS_APPROX(m2, m1 + symmLo.template selfadjointView<Lower>().llt().solve(matB));
182 m2.noalias() -= symmLo.template selfadjointView<Lower>().llt().solve(matB);
183 VERIFY_IS_APPROX(m2, m1 - symmLo.template selfadjointView<Lower>().llt().solve(matB));
|
| sparse_product.cpp | 167 VERIFY_IS_APPROX(x=mUp.template selfadjointView<Upper>()*b, refX=refS*b);
168 VERIFY_IS_APPROX(x=mLo.template selfadjointView<Lower>()*b, refX=refS*b);
169 VERIFY_IS_APPROX(x=mS.template selfadjointView<Upper|Lower>()*b, refX=refS*b);
|
| /external/eigen/unsupported/test/ |
| mpreal_support.cpp | 39 X = S.selfadjointView<Lower>().llt().solve(B);
40 VERIFY_IS_APPROX((S.selfadjointView<Lower>()*X).eval(),B);
49 VERIFY_IS_APPROX((S.selfadjointView<Lower>() * eig.eigenvectors()),
|
| /external/eigen/Eigen/src/Eigenvalues/ |
| GeneralizedSelfAdjointEigenSolver.h | 185 MatrixType matC = matA.template selfadjointView<Lower>();
198 MatrixType matC = matA.template selfadjointView<Lower>();
211 MatrixType matC = matA.template selfadjointView<Lower>();
|
| MatrixBaseEigenvalues.h | 56 * The SelfAdjointView class provides a better algorithm for selfadjoint
63 * SelfAdjointView::eigenvalues()
88 inline typename SelfAdjointView<MatrixType, UpLo>::EigenvaluesReturnType
89 SelfAdjointView<MatrixType, UpLo>::eigenvalues() const
91 typedef typename SelfAdjointView<MatrixType, UpLo>::PlainObject PlainObject;
111 * by SelfAdjointView::eigenvalues(), to compute the operator norm of a
112 * matrix. The SelfAdjointView class provides a better algorithm for
118 * \sa SelfAdjointView::eigenvalues(), SelfAdjointView::operatorNorm()
129 .template selfadjointView<Lower>(
[all...] |
| /external/ceres-solver/internal/ceres/ |
| dense_normal_cholesky_solver.cc | 85 lhs.selfadjointView<Eigen::Upper>().rankUpdate(Aref.transpose());
100 lhs.selfadjointView<Eigen::Upper>().llt().solve(rhs);
|
| line_search_direction.cc | 258 inverse_hessian_.selfadjointView<Eigen::Lower>());
263 inverse_hessian_.selfadjointView<Eigen::Lower>() *
267 B.selfadjointView<Eigen::Lower>().
278 inverse_hessian_.selfadjointView<Eigen::Lower>() *
|
| implicit_schur_complement_test.cc | 112 schur_solution = lhs->selfadjointView<Eigen::Upper>().llt().solve(*rhs);
159 lhs.selfadjointView<Eigen::Upper>().llt().solve(rhs);
|
| block_jacobi_preconditioner.cc | 97 // col_block_size).selfadjointView<Eigen::Upper>().rankUpdate(m);
113 block = block.selfadjointView<Eigen::Upper>()
|
| schur_jacobi_preconditioner.cc | 130 .selfadjointView<Eigen::Upper>()
|
| schur_eliminator_test.cc | 162 .selfadjointView<Eigen::Upper>()
176 Matrix delta = (lhs_ref - lhs_expected).selfadjointView<Eigen::Upper>();
|
| implicit_schur_complement.cc | 163 .selfadjointView<Eigen::Upper>()
|
| /external/eigen/blas/ |
| level2_real_impl.h | 44 if(UPLO(*uplo)==UP) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Upper>() * (alpha * vector(actual_x,*n));
45 else if(UPLO(*uplo)==LO) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Lower>() * (alpha * vector(actual_x,*n));
92 // if(UPLO(*uplo)==LO) matrix(c,*n,*n,*ldc).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n), alpha);
93 // else if(UPLO(*uplo)==UP) matrix(c,*n,*n,*ldc).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n), alpha);
146 if(UPLO(*uplo)==LO) matrix(c,*n,*n,*ldc).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n), vector(y_cpy,*n), alpha);
147 else if(UPLO(*uplo)==UP) matrix(c,*n,*n,*ldc).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n), vector(y_cpy,*n), alpha);
|
| level2_cplx_impl.h | 52 if(UPLO(*uplo)==UP) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Upper>() * (alpha * vector(actual_x,*n));
53 else if(UPLO(*uplo)==LO) vector(actual_y,*n).noalias() += matrix(a,*n,*n,*lda).selfadjointView<Lower>() * (alpha * vector(actual_x,*n));
138 // if(UPLO(*uplo)==LO) matrix(a,*n,*n,*lda).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n), alpha);
139 // else if(UPLO(*uplo)==UP) matrix(a,*n,*n,*lda).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n), alpha);
185 if(UPLO(*uplo)==LO) matrix(a,*n,*n,*lda).selfadjointView<Lower>().rankUpdate(vector(x_cpy,*n),vector(y_cpy,*n),alpha);
186 else if(UPLO(*uplo)==UP) matrix(a,*n,*n,*lda).selfadjointView<Upper>().rankUpdate(vector(x_cpy,*n),vector(y_cpy,*n),alpha);
|
| /external/eigen/unsupported/Eigen/src/SparseExtra/ |
| MatrixMarketIterator.h | 93 m_mat = B.template selfadjointView<Lower>();
|
