| /external/eigen/doc/snippets/ |
| VectorwiseOp_homogeneous.cpp | 5 cout << "M.colwise().homogeneous():" << endl << M.colwise().homogeneous() << endl << endl;
6 cout << "P * M.colwise().homogeneous():" << endl << P * M.colwise().homogeneous() << endl << endl;
7 cout << "P * M.colwise().homogeneous().hnormalized(): " << endl << (P * M.colwise().homogeneous()).colwise().hnormalized() << endl << endl
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| PartialRedux_maxCoeff.cpp | 3 cout << "Here is the maximum of each column:" << endl << m.colwise().maxCoeff() << endl;
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| PartialRedux_minCoeff.cpp | 3 cout << "Here is the minimum of each column:" << endl << m.colwise().minCoeff() << endl;
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| PartialRedux_norm.cpp | 3 cout << "Here is the norm of each column:" << endl << m.colwise().norm() << endl;
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| MatrixBase_colwise.cpp | 3 cout << "Here is the sum of each column:" << endl << m.colwise().sum() << endl;
5 << endl << m.cwiseAbs().colwise().maxCoeff() << endl;
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| DirectionWise_replicate.cpp | 3 cout << "m.colwise().replicate<3>() = ..." << endl;
4 cout << m.colwise().replicate<3>() << endl;
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| DirectionWise_hnormalized.cpp | 5 cout << "M.colwise().hnormalized():" << endl << M.colwise().hnormalized() << endl << endl;
7 cout << "(P*M).colwise().hnormalized():" << endl << (P*M).colwise().hnormalized() << endl << endl
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| Vectorwise_reverse.cpp | 4 cout << "Here is the colwise reverse of m:" << endl << m.colwise().reverse() << endl;
9 //m.colwise().reverse()(1,0) = 4;
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| /external/eigen/doc/examples/ |
| Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp | 20 (m.colwise() - v).colwise().squaredNorm().minCoeff(&index);
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| Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp | 13 cout << "1-norm(m) = " << m.cwiseAbs().colwise().sum().maxCoeff()
14 << " == " << m.colwise().lpNorm<1>().maxCoeff() << endl;
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| Tutorial_ReductionsVisitorsBroadcasting_colwise.cpp | 12 << mat.colwise().maxCoeff() << std::endl;
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| Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple.cpp | 17 mat.colwise() += v;
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| Tutorial_ReductionsVisitorsBroadcasting_maxnorm.cpp | 13 float maxNorm = mat.colwise().sum().maxCoeff(&maxIndex);
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| /external/eigen/test/ |
| geo_homogeneous.cpp | 47 VERIFY_IS_APPROX(m0.colwise().homogeneous(), hm0);
48 VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized());
52 VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized());
56 VERIFY_IS_APPROX(t1 * (m0.colwise().homogeneous().eval()), t1 * m0.colwise().homogeneous());
60 VERIFY_IS_APPROX(t2 * (m0.colwise().homogeneous().eval()), t2 * m0.colwise().homogeneous());
86 pts1 = pts.colwise().homogeneous();
87 VERIFY_IS_APPROX(aff * pts.colwise().homogeneous(), (aff * pts1).colwise().hnormalized())
[all...] |
| vectorwiseop.cpp | 38 m2.colwise() += colvec;
39 VERIFY_IS_APPROX(m2, m1.colwise() + colvec);
42 VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose());
43 VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose());
56 m2.colwise() -= colvec;
57 VERIFY_IS_APPROX(m2, m1.colwise() - colvec);
60 VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose());
61 VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose());
74 m2.colwise() *= colvec;
75 VERIFY_IS_APPROX(m2, m1.colwise() * colvec)
[all...] |
| geo_orthomethods.cpp | 47 // colwise/rowwise cross product
52 mcross = mat3.colwise().cross(vec3);
55 VERIFY_IS_MUCH_SMALLER_THAN((mat3.adjoint() * mat3.colwise().cross(vec3)).diagonal().cwiseAbs().sum(), Scalar(1));
56 VERIFY_IS_MUCH_SMALLER_THAN((mat3.adjoint() * mat3.colwise().cross(Vector3::Random())).diagonal().cwiseAbs().sum(), Scalar(1));
58 VERIFY_IS_MUCH_SMALLER_THAN((vec3.adjoint() * mat3.colwise().cross(vec3)).cwiseAbs().sum(), Scalar(1));
59 VERIFY_IS_MUCH_SMALLER_THAN((vec3.adjoint() * Matrix3::Random().colwise().cross(vec3)).cwiseAbs().sum(), Scalar(1));
103 // colwise/rowwise cross product
109 mcross3N = mat3N.colwise().cross(vec3);
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| array_for_matrix.cpp | 44 VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum().sum() - m1.sum(), m1.squaredNorm());
46 VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1+m2).squaredNorm());
48 VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>()));
52 VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1);
54 VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1)
[all...] |
| stable_norm.cpp | 102 VERIFY_IS_APPROX(vrand.colwise().stableNorm(), vrand.colwise().norm());
103 VERIFY_IS_APPROX(vrand.colwise().blueNorm(), vrand.colwise().norm());
104 VERIFY_IS_APPROX(vrand.colwise().hypotNorm(), vrand.colwise().norm());
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| array_replicate.cpp | 56 vx1=m2+(m2.colwise().replicate(1));
69 VERIFY_IS_APPROX(vx1, v1.colwise().replicate(f2));
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| array_reverse.cpp | 76 MatrixType m1_cr = m1.colwise().reverse();
77 // Verify that PartialRedux::reverse() works (for colwise())
117 m2.colwise().reverseInPlace();
118 VERIFY_IS_APPROX(m2,m1.colwise().reverse().eval());
120 m1.colwise().reverse()(r, c) = x;
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| array.cpp | 69 VERIFY_IS_APPROX(m1.abs().colwise().sum().sum(), m1.abs().sum());
72 VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.colwise().sum().sum() - m1.sum()), m1.abs().sum());
76 VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>()));
80 VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1);
82 VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1);
202 // TODO allows colwise/rowwise for array
203 VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayOfIndices::Constant(cols,rows).transpose())
[all...] |
| /external/eigen/Eigen/src/Geometry/ |
| Umeyama.h | 122 const RowMajorMatrixType src_demean = src.colwise() - src_mean;
123 const RowMajorMatrixType dst_demean = dst.colwise() - dst_mean;
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| /external/eigen/doc/ |
| tutorial.cpp | 45 std::cout << "m4.colwise().sum():\n" << m4.colwise().sum() << std::endl;
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| /external/eigen/unsupported/test/ |
| cxx11_tensor_forced_eval.cpp | 54 output.rowwise() -= input.colwise().maxCoeff();
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| /external/eigen/Eigen/src/Core/ |
| Reverse.h | 175 xpr.topRows(half).swap(xpr.bottomRows(half).colwise().reverse());
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