/external/eigen/test/ |
D | vectorwiseop.cpp | 38 m2.colwise() += colvec; in vectorwiseop_array() 39 VERIFY_IS_APPROX(m2, m1.colwise() + colvec); in vectorwiseop_array() 42 VERIFY_RAISES_ASSERT(m2.colwise() += colvec.transpose()); in vectorwiseop_array() 43 VERIFY_RAISES_ASSERT(m1.colwise() + colvec.transpose()); in vectorwiseop_array() 56 m2.colwise() -= colvec; in vectorwiseop_array() 57 VERIFY_IS_APPROX(m2, m1.colwise() - colvec); in vectorwiseop_array() 60 VERIFY_RAISES_ASSERT(m2.colwise() -= colvec.transpose()); in vectorwiseop_array() 61 VERIFY_RAISES_ASSERT(m1.colwise() - colvec.transpose()); in vectorwiseop_array() 74 m2.colwise() *= colvec; in vectorwiseop_array() 75 VERIFY_IS_APPROX(m2, m1.colwise() * colvec); in vectorwiseop_array() [all …]
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D | geo_homogeneous.cpp | 47 VERIFY_IS_APPROX(m0.colwise().homogeneous(), hm0); in homogeneous() 48 VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); in homogeneous() 52 VERIFY_IS_APPROX(m0, hm0.colwise().hnormalized()); in homogeneous() 56 VERIFY_IS_APPROX(t1 * (m0.colwise().homogeneous().eval()), t1 * m0.colwise().homogeneous()); in homogeneous() 60 VERIFY_IS_APPROX(t2 * (m0.colwise().homogeneous().eval()), t2 * m0.colwise().homogeneous()); in homogeneous() 86 pts1 = pts.colwise().homogeneous(); in homogeneous() 87 VERIFY_IS_APPROX(aff * pts.colwise().homogeneous(), (aff * pts1).colwise().hnormalized()); in homogeneous() 88 VERIFY_IS_APPROX(caff * pts.colwise().homogeneous(), (caff * pts1).colwise().hnormalized()); in homogeneous() 89 VERIFY_IS_APPROX(proj * pts.colwise().homogeneous(), (proj * pts1)); in homogeneous() 91 VERIFY_IS_APPROX((aff * pts1).colwise().hnormalized(), aff * pts); in homogeneous() [all …]
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D | geo_orthomethods.cpp | 52 mcross = mat3.colwise().cross(vec3); in orthomethods_3() 55 …VERIFY_IS_MUCH_SMALLER_THAN((mat3.adjoint() * mat3.colwise().cross(vec3)).diagonal().cwiseAbs().su… in orthomethods_3() 56 …VERIFY_IS_MUCH_SMALLER_THAN((mat3.adjoint() * mat3.colwise().cross(Vector3::Random())).diagonal().… in orthomethods_3() 58 …VERIFY_IS_MUCH_SMALLER_THAN((vec3.adjoint() * mat3.colwise().cross(vec3)).cwiseAbs().sum(), Scalar… in orthomethods_3() 59 …VERIFY_IS_MUCH_SMALLER_THAN((vec3.adjoint() * Matrix3::Random().colwise().cross(vec3)).cwiseAbs().… in orthomethods_3() 109 mcross3N = mat3N.colwise().cross(vec3); in orthomethods()
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D | array_for_matrix.cpp | 44 VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum().sum() - m1.sum(), m1.squaredNorm()); in array_for_matrix() 46 …VERIFY_IS_MUCH_SMALLER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1… in array_for_matrix() 48 …VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>())); in array_for_matrix() 52 VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1); in array_for_matrix() 54 VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1); in array_for_matrix() 61 VERIFY_IS_APPROX(m1.block(0,0,0,cols).colwise().sum(), RowVectorType::Zero(cols)); in array_for_matrix() 146 …VERIFY_IS_APPROX(((m1.array().abs()+1)>RealScalar(0.1)).matrix().colwise().count(), VectorOfIndice… in comparisons()
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D | stable_norm.cpp | 102 VERIFY_IS_APPROX(vrand.colwise().stableNorm(), vrand.colwise().norm()); in stable_norm() 103 VERIFY_IS_APPROX(vrand.colwise().blueNorm(), vrand.colwise().norm()); in stable_norm() 104 VERIFY_IS_APPROX(vrand.colwise().hypotNorm(), vrand.colwise().norm()); in stable_norm()
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D | array_reverse.cpp | 76 MatrixType m1_cr = m1.colwise().reverse(); in reverse() 117 m2.colwise().reverseInPlace(); in reverse() 118 VERIFY_IS_APPROX(m2,m1.colwise().reverse().eval()); in reverse() 120 m1.colwise().reverse()(r, c) = x; in reverse()
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D | cuda_basic.cu | 75 MapType(out+i*stride+1*step, x1.rows()*3, x1.cols()) = in[i] * x1.colwise().replicate(3); in operator ()() 94 out[i*N+6] = x1.colwise().sum().maxCoeff(); in operator ()() 96 out[i*N+8] = x1.matrix().colwise().squaredNorm().sum(); in operator ()()
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D | array_replicate.cpp | 56 vx1=m2+(m2.colwise().replicate(1)); in replicate() 69 VERIFY_IS_APPROX(vx1, v1.colwise().replicate(f2)); in replicate()
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D | array.cpp | 69 VERIFY_IS_APPROX(m1.abs().colwise().sum().sum(), m1.abs().sum()); in array() 72 VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.colwise().sum().sum() - m1.sum()), m1.abs().sum()); in array() 76 …VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::scalar_sum_op<Scalar,Scalar>())); in array() 80 VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1); in array() 82 VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1); in array() 203 …VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayOfIndices::Constant(cols,r… in comparisons()
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/external/eigen/doc/snippets/ |
D | 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 ….colwise().homogeneous().hnormalized(): " << endl << (P * M.colwise().homogeneous()).colwise().hno…
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D | 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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D | 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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D | PartialRedux_maxCoeff.cpp | 3 cout << "Here is the maximum of each column:" << endl << m.colwise().maxCoeff() << endl;
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D | PartialRedux_minCoeff.cpp | 3 cout << "Here is the minimum of each column:" << endl << m.colwise().minCoeff() << endl;
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D | PartialRedux_norm.cpp | 3 cout << "Here is the norm of each column:" << endl << m.colwise().norm() << endl;
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D | DirectionWise_replicate.cpp | 4 cout << m.colwise().replicate<3>() << endl;
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D | Vectorwise_reverse.cpp | 4 cout << "Here is the colwise reverse of m:" << endl << m.colwise().reverse() << endl;
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/external/eigen/doc/ |
D | TutorialReductionsVisitorsBroadcasting.dox | 110 with \link DenseBase::colwise() colwise() \endlink or \link DenseBase::rowwise() rowwise() \endlink. 152 though the \link DenseBase::colwise() colwise() \endlink visitor, obtaining a new matrix whose 164 \mbox{m.colwise().sum()} = \begin{bmatrix} 4 & 3 & 13 & 11 \end{bmatrix} 189 We can interpret the instruction <tt>mat.colwise() += v</tt> in two equivalent ways. It adds the ve… 239 (m.colwise() - v).colwise().squaredNorm().minCoeff(&index); 244 …- <tt>m.colwise() - v</tt> is a broadcasting operation, subtracting <tt>v</tt> from each column in… 246 \mbox{m.colwise() - v} = 253 …- <tt>(m.colwise() - v).colwise().squaredNorm()</tt> is a partial reduction, computing the squared… 255 \mbox{(m.colwise() - v).colwise().squaredNorm()} =
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D | FunctionsTakingEigenTypes.dox | 99 const RowVectorXf x_mean = x.colwise().sum() / num_observations; 100 const RowVectorXf y_mean = y.colwise().sum() / num_observations; 119 const RowVectorXf x_mean = x.colwise().sum() / num_observations; 120 const RowVectorXf y_mean = y.colwise().sum() / num_observations; 142 const RowVectorXf x_mean = x.colwise().sum() / num_observations; 143 const RowVectorXf y_mean = y.colwise().sum() / num_observations; 164 const RowVectorType x_mean = x.colwise().sum() / num_observations; 165 const RowVectorType y_mean = y.colwise().sum() / num_observations; 196 const RowVectorType x_mean = x.colwise().sum() / num_observations; 197 const RowVectorType y_mean = y.colwise().sum() / num_observations;
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D | AsciiQuickReference.txt | 96 R.transpose().colwise().reverse() // rot90(R) // Read-write 98 R.colwise().reverse() // flipud(R) 155 R.colwise().sum() // sum(R) 158 R.colwise().prod() // prod(R) 162 R.colwise().all() // all(R) 165 R.colwise().any() // any(R)
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/external/eigen/doc/examples/ |
D | Tutorial_ReductionsVisitorsBroadcasting_reductions_operatornorm.cpp | 13 cout << "1-norm(m) = " << m.cwiseAbs().colwise().sum().maxCoeff() in main() 14 << " == " << m.colwise().lpNorm<1>().maxCoeff() << endl; in main()
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D | Tutorial_ReductionsVisitorsBroadcasting_broadcast_1nn.cpp | 20 (m.colwise() - v).colwise().squaredNorm().minCoeff(&index); in main()
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D | Tutorial_ReductionsVisitorsBroadcasting_colwise.cpp | 12 << mat.colwise().maxCoeff() << std::endl; in main()
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D | Tutorial_ReductionsVisitorsBroadcasting_broadcast_simple.cpp | 17 mat.colwise() += v; in main()
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/external/eigen/Eigen/src/Geometry/ |
D | Umeyama.h | 122 const RowMajorMatrixType src_demean = src.colwise() - src_mean; 123 const RowMajorMatrixType dst_demean = dst.colwise() - dst_mean;
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