| /external/eigen/Eigen/src/Core/ |
| D | Dot.h | 93 …umTraits<typename internal::traits<Derived>::Scalar>::Real MatrixBase<Derived>::squaredNorm() const
107 return numext::sqrt(squaredNorm());
125 RealScalar z = n.squaredNorm();
144 RealScalar z = squaredNorm();
169 RealScalar z = (n/w).squaredNorm();
191 RealScalar z = (derived()/w).squaredNorm();
284 …t::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm();
304 if(!internal::isApprox(self.col(i).squaredNorm(), static_cast<RealScalar>(1), prec))
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| /external/eigen/test/ |
| D | stable_norm.cpp | 89 …VERIFY_IS_NOT_APPROX(sqrt(copy(vbig.squaredNorm())), abs(sqrt(size)*big)); // here the default nor… in stable_norm()
96 …VERIFY_IS_NOT_APPROX(sqrt(copy(vsmall.squaredNorm())), abs(sqrt(size)*small)); // here the defau… in stable_norm()
118 VERIFY(!(numext::isfinite)(v.squaredNorm())); VERIFY((numext::isnan)(v.squaredNorm())); in stable_norm()
129 VERIFY(!(numext::isfinite)(v.squaredNorm())); VERIFY(isPlusInf(v.squaredNorm())); in stable_norm()
143 VERIFY(!(numext::isfinite)(v.squaredNorm())); VERIFY(isPlusInf(v.squaredNorm())); in stable_norm()
160 VERIFY(!(numext::isfinite)(v.squaredNorm())); VERIFY((numext::isnan)(v.squaredNorm())); in stable_norm()
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| D | cuda_basic.cu | 92 out[i*N+4] = x1.matrix().squaredNorm(); in operator ()()
96 out[i*N+8] = x1.matrix().colwise().squaredNorm().sum(); in operator ()()
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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()
45 VERIFY_IS_MUCH_SMALLER_THAN(m1.rowwise().sum().sum() - m1.sum(), m1.squaredNorm()); in array_for_matrix()
46 …LER_THAN(m1.colwise().sum() + m2.colwise().sum() - (m1+m2).colwise().sum(), (m1+m2).squaredNorm()); in array_for_matrix()
47 …LER_THAN(m1.rowwise().sum() - m2.rowwise().sum() - (m1-m2).rowwise().sum(), (m1-m2).squaredNorm()); in array_for_matrix()
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| D | sparse_vector.cpp | 96 VERIFY_IS_APPROX(v1.squaredNorm(), refV1.squaredNorm()); in sparse_vector()
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| D | geo_alignedbox.cpp | 127 VERIFY_IS_APPROX( 53.0f, box.diagonal().squaredNorm() ); in specificTest1()
154 VERIFY_IS_APPROX( 62, box.diagonal().squaredNorm() ); in specificTest2()
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| D | eigensolver_complex.cpp | 65 …ion<RealScalar>()*test_precision<RealScalar>()*numext::maxi(vec1.squaredNorm(),vec2.squaredNorm()); in verify_is_approx_upto_permutation()
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| /external/eigen/unsupported/test/ |
| D | levenberg_marquardt.cpp | 302 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 5.1304802941E+02); in testNistChwirut2()
323 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 5.1304802941E+02); in testNistChwirut2()
382 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.2455138894E-01); in testNistMisra1a()
399 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.2455138894E-01); in testNistMisra1a()
473 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.5324382854E+00); in testNistHahn1()
495 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 1.5324382854E+00); in testNistHahn1()
559 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 5.6419295283E-02); in testNistMisra1d()
576 VERIFY_IS_APPROX(lm.fvec().squaredNorm(), 5.6419295283E-02); in testNistMisra1d()
637 VERIFY(lm.fvec().squaredNorm() <= 1.4307867721E-25); in testNistLanczos1()
658 VERIFY(lm.fvec().squaredNorm() <= 1.4307867721E-25); in testNistLanczos1()
[all …]
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| D | NonLinearOptimization.cpp | 692 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.1304802941E+02); in testNistChwirut2()
713 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.1304802941E+02); in testNistChwirut2()
772 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.2455138894E-01); in testNistMisra1a()
789 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.2455138894E-01); in testNistMisra1a()
862 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.5324382854E+00); in testNistHahn1()
884 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 1.5324382854E+00); in testNistHahn1()
948 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6419295283E-02); in testNistMisra1d()
965 VERIFY_IS_APPROX(lm.fvec.squaredNorm(), 5.6419295283E-02); in testNistMisra1d()
1027 std::cout << lm.fvec.squaredNorm() << "\n"; in testNistLanczos1()
1028 VERIFY(lm.fvec.squaredNorm() <= 1.4307867721E-25); in testNistLanczos1()
[all …]
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| D | BVH.cpp | 55 if((b.center - p).squaredNorm() < SQR(b.radius)) in intersectObject()
72 if((b.center - v).squaredNorm() < SQR(b.radius)) in intersectObjectObject()
78 …ect(const BallType &b) { ++calls; return (std::max)(0., (b.center - p).squaredNorm() - SQR(b.radiu… in minimumOnObject()
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| /external/eigen/Eigen/src/SparseCore/ |
| D | SparseFuzzy.h | 24 …return (actualA - actualB).squaredNorm() <= prec * prec * numext::mini(actualA.squaredNorm(), actu… in isApprox()
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| D | SparseDot.h | 77 SparseMatrixBase<Derived>::squaredNorm() const in squaredNorm() function
87 return sqrt(squaredNorm()); in norm()
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| /external/eigen/Eigen/src/IterativeLinearSolvers/ |
| D | BiCGSTAB.h | 45 RealScalar r0_sqnorm = r0.squaredNorm(); in bicgstab()
46 RealScalar rhs_sqnorm = rhs.squaredNorm(); in bicgstab()
67 while ( r.squaredNorm() > tol2 && i<maxIters ) in bicgstab()
78 rho = r0_sqnorm = r.squaredNorm(); in bicgstab()
95 RealScalar tmp = t.squaredNorm(); in bicgstab()
104 tol_error = sqrt(r.squaredNorm()/rhs_sqnorm); in bicgstab()
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| D | LeastSquareConjugateGradient.h | 46 RealScalar rhsNorm2 = (mat.adjoint()*rhs).squaredNorm(); in least_square_conjugate_gradient()
55 RealScalar residualNorm2 = normal_residual.squaredNorm(); in least_square_conjugate_gradient()
73 Scalar alpha = absNew / tmp.squaredNorm(); // the amount we travel on dir in least_square_conjugate_gradient()
78 residualNorm2 = normal_residual.squaredNorm(); in least_square_conjugate_gradient()
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| D | ConjugateGradient.h | 45 RealScalar rhsNorm2 = rhs.squaredNorm(); in conjugate_gradient()
54 RealScalar residualNorm2 = residual.squaredNorm(); in conjugate_gradient()
76 residualNorm2 = residual.squaredNorm(); in conjugate_gradient()
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| /external/eigen/doc/examples/ |
| D | Tutorial_ReductionsVisitorsBroadcasting_reductions_norm.cpp | 18 cout << "v.squaredNorm() = " << v.squaredNorm() << endl; in main()
24 cout << "m.squaredNorm() = " << m.squaredNorm() << 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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| /external/eigen/doc/snippets/ |
| D | Tutorial_Map_using.cpp | 15 cout << "Squared euclidean distance: " << (m1-m2).squaredNorm() << endl;
17 (m1-m2map).squaredNorm() << endl;
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| D | PartialRedux_squaredNorm.cpp | 3 cout << "Here is the square norm of each row:" << endl << m.rowwise().squaredNorm() << endl;
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| /external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
| D | IterationController.h | 134 { return converged(v.squaredNorm()); } in converged()
148 { return finished(double(v.squaredNorm())); } in finished()
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| D | MINRES.h | 41 const RealScalar rhsNorm2(rhs.squaredNorm()); in minres()
59 RealScalar residualNorm2(v_new.squaredNorm()); in minres()
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| /external/eigen/doc/ |
| D | TutorialReductionsVisitorsBroadcasting.dox | 29 …\f$) squared norm of a vector can be obtained \link MatrixBase::squaredNorm() squaredNorm() \endli…
31 …link method, which returns the square root of \link MatrixBase::squaredNorm() squaredNorm() \endli…
226 …ean distance with the partial reduction named \link MatrixBase::squaredNorm() squaredNorm() \endli…
239 (m.colwise() - v).colwise().squaredNorm().minCoeff(&index);
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 | CustomizingEigen_Plugins.dox | 28 inline RealScalar squaredLength() const { return squaredNorm(); }
30 inline RealScalar invLength(void) const { return fast_inv_sqrt(squaredNorm()); }
34 { return (derived() - other.derived()).squaredNorm(); }
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| /external/eigen/unsupported/Eigen/ |
| D | AlignedVector3 | 173 inline Scalar squaredNorm() const
176 return m_coeffs.squaredNorm();
182 return sqrt(squaredNorm());
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| /external/eigen/unsupported/doc/examples/ |
| D | BVH_Example.cpp | 20 …OnObjectObject(const Vector2d &v1, const Vector2d &v2) { ++calls; return (v1 - v2).squaredNorm(); } in minimumOnObjectObject()
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