| /external/ceres-solver/examples/ |
| H A D | ellipse_approximation.cc | 407 (X.rowwise() - kY.row(i)).rowwise().squaredNorm().minCoeff(&t[i]);
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| /external/eigen/Eigen/src/Core/ |
| H A D | DenseBase.h | 440 ConstRowwiseReturnType rowwise() const;
441 RowwiseReturnType rowwise();
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| H A D | VectorwiseOp.h | 158 * It is the return type of DenseBase::colwise() and DenseBase::rowwise()
164 * \sa DenseBase::colwise(), DenseBase::rowwise(), class PartialReduxExpr
272 * \sa class VectorwiseOp, DenseBase::colwise(), DenseBase::rowwise()
595 * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
606 * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting
624 DenseBase<Derived>::rowwise() const function in class:Eigen::DenseBase
635 DenseBase<Derived>::rowwise() function in class:Eigen::DenseBase
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| /external/eigen/Eigen/src/Geometry/ |
| H A D | Homogeneous.h | 256 dst += m_lhs.col(m_lhs.cols()-1).rowwise()
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| H A D | Umeyama.h | 119 const VectorType src_mean = src.rowwise().sum() * one_over_n;
120 const VectorType dst_mean = dst.rowwise().sum() * one_over_n;
127 const Scalar src_var = src_demean.rowwise().squaredNorm().sum() * one_over_n;
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| /external/eigen/doc/examples/ |
| H A D | Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple_rowwise.cpp | 16 mat.rowwise() += v.transpose();
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| H A D | Tutorial_ReductionsVisitorsBroadcasting_rowwise.cpp | 12 << mat.rowwise().maxCoeff() << std::endl;
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| /external/eigen/doc/snippets/ |
| H A D | DirectionWise_replicate_int.cpp | 3 cout << "v.rowwise().replicate(5) = ..." << endl;
4 cout << v.rowwise().replicate(5) << endl;
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| H A D | MatrixBase_rowwise.cpp | 3 cout << "Here is the sum of each row:" << endl << m.rowwise().sum() << endl;
5 << endl << m.cwiseAbs().rowwise().maxCoeff() << endl;
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| H A D | PartialRedux_count.cpp | 3 cout << "Here is the count of elements larger or equal than 0.5 of each row:" << endl << (m.array() >= 0.5).rowwise().count() << endl;
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| H A D | PartialRedux_prod.cpp | 3 cout << "Here is the product of each row:" << endl << m.rowwise().prod() << endl;
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| H A D | PartialRedux_squaredNorm.cpp | 3 cout << "Here is the square norm of each row:" << endl << m.rowwise().squaredNorm() << endl;
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| H A D | PartialRedux_sum.cpp | 3 cout << "Here is the sum of each row:" << endl << m.rowwise().sum() << endl;
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| H A D | Vectorwise_reverse.cpp | 3 cout << "Here is the rowwise reverse of m:" << endl << m.rowwise().reverse() << endl;
7 << m.rowwise().reverse()(1,0) << endl;
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| /external/eigen/doc/ |
| H A D | tutorial.cpp | 46 std::cout << "m4.rowwise().sum():\n" << m4.rowwise().sum() << std::endl;
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| /external/eigen/test/ |
| H A D | array.cpp | 67 VERIFY_IS_APPROX(m1.abs().rowwise().sum().sum(), m1.abs().sum());
70 VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.rowwise().sum().sum() - m1.sum()), m1.abs().sum());
72 VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
81 VERIFY_IS_APPROX(m3.rowwise() += rv1, m1.rowwise() + rv1);
83 VERIFY_IS_APPROX(m3.rowwise() -= rv1, m1.rowwise() - rv1);
147 // TODO allows colwise/rowwise for array
149 VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayOfIndices::Constant(rows, cols));
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| H A D | array_for_matrix.cpp | 45 VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum().sum() - m1.sum(), m1.squaredNorm());
47 VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum() - m2.rowwise().sum() - (m1-m2).rowwise().sum(), (m1-m2).squaredNorm());
56 VERIFY_IS_APPROX(m3.rowwise() += rv1, m1.rowwise() + rv1);
58 VERIFY_IS_APPROX(m3.rowwise() -= rv1, m1.rowwise() - rv1);
62 VERIFY_IS_APPROX(m1.block(0,0,rows,0).rowwise().prod(), ColVectorType::Ones(rows));
128 // TODO allows colwise/rowwise fo
[all...] |
| H A D | array_replicate.cpp | 51 VERIFY_IS_APPROX(x2, v1.rowwise().replicate(f1));
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| H A D | array_reverse.cpp | 84 MatrixType m1_rr = m1.rowwise().reverse();
85 // Verify that PartialRedux::reverse() works (for rowwise())
104 m1.rowwise().reverse()(r, c) = x;
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| H A D | geo_homogeneous.cpp | 58 VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t2,
59 v0.transpose().rowwise().homogeneous() * t2);
60 m0.transpose().rowwise().homogeneous().eval();
61 VERIFY_IS_APPROX((m0.transpose().rowwise().homogeneous().eval()) * t2,
62 m0.transpose().rowwise().homogeneous() * t2);
65 VERIFY_IS_APPROX((v0.transpose().rowwise().homogeneous().eval()) * t3,
66 v0.transpose().rowwise().homogeneous() * t3);
67 VERIFY_IS_APPROX((m0.transpose().rowwise().homogeneous().eval()) * t3,
68 m0.transpose().rowwise().homogeneous() * t3);
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| H A D | geo_orthomethods.cpp | 43 // colwise/rowwise cross product
50 mcross = mat3.rowwise().cross(vec3);
91 // colwise/rowwise cross product
102 mcrossN3 = matN3.rowwise().cross(vec3);
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| H A D | householder.cpp | 69 m3.rowwise() = v1.transpose();
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| /external/eigen/test/eigen2/ |
| H A D | eigen2_array.cpp | 46 VERIFY_IS_APPROX(m1.rowwise().sum().sum(), m1.sum());
48 VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum());
104 VERIFY_IS_APPROX(((m1.cwise().abs().cwise()+1).cwise()>RealScalar(0.1)).rowwise().count().template cast<int>(), VectorXi::Constant(rows, cols));
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| H A D | eigen2_geometry.cpp | 412 // colwise/rowwise cross product
419 mcross = mat3.rowwise().cross(vec3);
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| H A D | eigen2_geometry_with_eigen2_prefix.cpp | 414 // colwise/rowwise cross product
421 mcross = mat3.rowwise().cross(vec3);
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