| /external/eigen/doc/snippets/ |
| tut_arithmetic_transpose_conjugate.cpp | 7 cout << "Here is the conjugate of a\n" << a.conjugate() << endl;
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| /external/eigen/test/ |
| product_extra.cpp | 52 VERIFY_IS_APPROX( m1.adjoint() * (s1*m2).conjugate(), (m1.adjoint()).eval() * ((s1*m2).conjugate()).eval());
55 // test all possible conjugate combinations for the four matrix-vector product cases:
57 VERIFY_IS_APPROX((-m1.conjugate() * s2) * (s1 * vc2),
58 (-m1.conjugate()*s2).eval() * (s1 * vc2).eval());
59 VERIFY_IS_APPROX((-m1 * s2) * (s1 * vc2.conjugate()),
60 (-m1*s2).eval() * (s1 * vc2.conjugate()).eval());
61 VERIFY_IS_APPROX((-m1.conjugate() * s2) * (s1 * vc2.conjugate()),
62 (-m1.conjugate()*s2).eval() * (s1 * vc2.conjugate()).eval())
[all...] |
| product_trsolve.cpp | 46 VERIFY_TRSM(cmLhs.conjugate().template triangularView<Lower>(), cmRhs);
50 VERIFY_TRSM(cmLhs.conjugate().template triangularView<Upper>(), rmRhs);
53 VERIFY_TRSM(cmLhs.conjugate().template triangularView<UnitLower>(), cmRhs);
57 VERIFY_TRSM(rmLhs.conjugate().template triangularView<UnitUpper>(), rmRhs);
60 VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<Lower>(), cmRhs);
63 VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<Upper>(), rmRhs);
65 VERIFY_TRSM_ONTHERIGHT(cmLhs.conjugate().template triangularView<UnitLower>(), cmRhs);
69 VERIFY_TRSM_ONTHERIGHT(rmLhs.conjugate().template triangularView<UnitUpper>(), rmRhs);
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| product_trmv.cpp | 44 VERIFY(((s1*m3).conjugate() * v1).isApprox((s1*m1).conjugate().template triangularView<Eigen::Lower>() * v1, largerEps));
46 VERIFY((m3.conjugate() * v1.conjugate()).isApprox(m1.conjugate().template triangularView<Eigen::Upper>() * v1.conjugate(), largerEps));
62 VERIFY((m3.adjoint() * (s1*v1.conjugate())).isApprox(m1.adjoint().template triangularView<Eigen::Upper>() * (s1*v1.conjugate()), largerEps));
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| adjoint.cpp | 17 Transpose.h Conjugate.h Dot.h
40 // check basic compatibility of adjoint, transpose, conjugate
41 VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1);
42 VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(), m1);
76 VERIFY_IS_APPROX(m1.conjugate()(r,c), internal::conj(m1(r,c)));
98 VERIFY_IS_APPROX(m3,m1.conjugate());
126 VERIFY_RAISES_ASSERT(a = a.conjugate().transpose());
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| product_trmm.cpp | 48 VERIFY_IS_APPROX( ge_xs.noalias() = (s1*mat.adjoint()).template triangularView<Mode>() * (s2*ge_left.transpose()), s1*triTr.conjugate() * (s2*ge_left.transpose()));
49 VERIFY_IS_APPROX( ge_sx.noalias() = ge_right.transpose() * mat.adjoint().template triangularView<Mode>(), ge_right.transpose() * triTr.conjugate());
51 VERIFY_IS_APPROX( ge_xs.noalias() = (s1*mat.adjoint()).template triangularView<Mode>() * (s2*ge_left.adjoint()), s1*triTr.conjugate() * (s2*ge_left.adjoint()));
52 VERIFY_IS_APPROX( ge_sx.noalias() = ge_right.adjoint() * mat.adjoint().template triangularView<Mode>(), ge_right.adjoint() * triTr.conjugate());
55 VERIFY_IS_APPROX( (ge_xs_save + s1*triTr.conjugate() * (s2*ge_left.adjoint())).eval(), ge_xs.noalias() += (s1*mat.adjoint()).template triangularView<Mode>() * (s2*ge_left.adjoint()) );
57 VERIFY_IS_APPROX( ge_sx_save - (ge_right.adjoint() * (-s1 * triTr).conjugate()).eval(), ge_sx.noalias() -= (ge_right.adjoint() * (-s1 * mat).adjoint().template triangularView<Mode>()).eval());
59 VERIFY_IS_APPROX( ge_xs = (s1*mat).adjoint().template triangularView<Mode>() * ge_left.adjoint(), internal::conj(s1) * triTr.conjugate() * ge_left.adjoint());
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| sparse_solvers.cpp | 60 VERIFY_IS_APPROX(refMat2.conjugate().template triangularView<Upper>().solve(vec2),
61 m2.conjugate().template triangularView<Upper>().solve(vec3));
66 VERIFY_IS_APPROX(refMat2.conjugate().template triangularView<Upper>().solve(vec2),
67 mm2.conjugate().template triangularView<Upper>().solve(vec3));
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| product_syrk.cpp | 68 VERIFY_IS_APPROX((m2.template selfadjointView<Lower>().rankUpdate(m1.col(c).conjugate(),s1)._expression()),
69 ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Lower>().toDenseMatrix()));
72 VERIFY_IS_APPROX((m2.template selfadjointView<Upper>().rankUpdate(m1.col(c).conjugate(),s1)._expression()),
73 ((s1 * m1.col(c).conjugate() * m1.col(c).conjugate().adjoint()).eval().template triangularView<Upper>().toDenseMatrix()));
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| triangular.cpp | 63 VERIFY_IS_APPROX(m3.template triangularView<Lower>().conjugate().toDenseMatrix(),
64 m3.conjugate().template triangularView<Lower>().toDenseMatrix());
79 VERIFY(v2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(v2)), largerEps));
89 VERIFY(m2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(m2)), largerEps));
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| cholesky.cpp | 113 VERIFY_IS_APPROX(MatrixType(chollo.matrixL().transpose().conjugate()), MatrixType(chollo.matrixU()));
114 VERIFY_IS_APPROX(MatrixType(chollo.matrixU().transpose().conjugate()), MatrixType(chollo.matrixL()));
115 VERIFY_IS_APPROX(MatrixType(cholup.matrixL().transpose().conjugate()), MatrixType(cholup.matrixU()));
116 VERIFY_IS_APPROX(MatrixType(cholup.matrixU().transpose().conjugate()), MatrixType(cholup.matrixL()));
145 VERIFY_IS_APPROX(MatrixType(ldltlo.matrixL().transpose().conjugate()), MatrixType(ldltlo.matrixU()));
146 VERIFY_IS_APPROX(MatrixType(ldltlo.matrixU().transpose().conjugate()), MatrixType(ldltlo.matrixL()));
147 VERIFY_IS_APPROX(MatrixType(ldltup.matrixL().transpose().conjugate()), MatrixType(ldltup.matrixU()));
148 VERIFY_IS_APPROX(MatrixType(ldltup.matrixU().transpose().conjugate()), MatrixType(ldltup.matrixL()));
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| product_symm.cpp | 68 VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs3).conjugate(),
69 rhs13 = (s1*m1.adjoint()) * (s2*rhs3).conjugate());
73 VERIFY_IS_APPROX(rhs12.noalias() += s1 * ((m2.adjoint()).template selfadjointView<Lower>() * (s2*rhs3).conjugate()),
74 rhs13 += (s1*m1.adjoint()) * (s2*rhs3).conjugate());
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| /prebuilts/python/darwin-x86/2.7.5/lib/python2.7/test/ |
| test_abstract_numbers.py | 15 self.assertEqual(7, int(7).conjugate())
25 self.assertEqual(7, long(7).conjugate())
35 self.assertEqual(7.3, float(7.3).conjugate())
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| /prebuilts/python/linux-x86/2.7.5/lib/python2.7/test/ |
| test_abstract_numbers.py | 15 self.assertEqual(7, int(7).conjugate())
25 self.assertEqual(7, long(7).conjugate())
35 self.assertEqual(7.3, float(7.3).conjugate())
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| /external/eigen/Eigen/src/Core/products/ |
| TriangularSolverVector.h | 17 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate, int StorageOrder>
18 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheRight, Mode, Conjugate, StorageOrder>
24 Conjugate,StorageOrder==RowMajor?ColMajor:RowMajor
30 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate>
31 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, RowMajor>
41 Conjugate,
61 general_matrix_vector_product<Index,LhsScalar,RowMajor,Conjugate,RhsScalar,false>::run(
84 template<typename LhsScalar, typename RhsScalar, typename Index, int Mode, bool Conjugate>
85 struct triangular_solve_vector<LhsScalar, RhsScalar, Index, OnTheLeft, Mode, Conjugate, ColMajor>
94 typename internal::conditional<Conjugate,
[all...] |
| TriangularSolverMatrix_MKL.h | 42 template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
43 struct triangular_solve_matrix<EIGTYPE,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor> \
49 conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
66 transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
76 a_tmp = tri.conjugate(); \
97 template <typename Index, int Mode, bool Conjugate, int TriStorageOrder> \
98 struct triangular_solve_matrix<EIGTYPE,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor> \
104 conjA = ((TriStorageOrder==ColMajor) && Conjugate) ? 1 : 0 \
121 transa = (TriStorageOrder==RowMajor) ? ((Conjugate) ? 'C' : 'T') : 'N'; \
131 a_tmp = tri.conjugate(); \
[all...] |
| TriangularSolverMatrix.h | 18 template <typename Scalar, typename Index, int Side, int Mode, bool Conjugate, int TriStorageOrder>
19 struct triangular_solve_matrix<Scalar,Index,Side,Mode,Conjugate,TriStorageOrder,RowMajor>
30 NumTraits<Scalar>::IsComplex && Conjugate,
38 template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
39 struct triangular_solve_matrix<Scalar,Index,OnTheLeft,Mode,Conjugate,TriStorageOrder,ColMajor>
68 conj_if<Conjugate> conj;
69 gebp_kernel<Scalar, Scalar, Index, Traits::mr, Traits::nr, Conjugate, false> gebp_kernel;
180 template <typename Scalar, typename Index, int Mode, bool Conjugate, int TriStorageOrder>
181 struct triangular_solve_matrix<Scalar,Index,OnTheRight,Mode,Conjugate,TriStorageOrder,ColMajor>
211 conj_if<Conjugate> conj
[all...] |
| GeneralMatrixMatrix_MKL.h | 94 a_tmp = lhs.conjugate(); \
101 b_tmp = rhs.conjugate(); \
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| SelfadjointMatrixMatrix_MKL.h | 133 a_tmp = lhs.conjugate(); \
144 b_tmp = rhs.conjugate(); \
258 a_tmp = rhs.conjugate(); \
269 b_tmp = lhs.conjugate(); \
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| /external/eigen/test/eigen2/ |
| eigen2_adjoint.cpp | 15 Transpose.h Conjugate.h Dot.h
43 // check basic compatibility of adjoint, transpose, conjugate
44 VERIFY_IS_APPROX(m1.transpose().conjugate().adjoint(), m1);
45 VERIFY_IS_APPROX(m1.adjoint().conjugate().transpose(), m1);
69 VERIFY_IS_APPROX(m1.conjugate()(r,c), ei_conj(m1(r,c)));
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| /external/ceres-solver/internal/ceres/ |
| conjugate_gradients_solver.h | 31 // Preconditioned Conjugate Gradients based solver for positive
45 // This class implements the now classical Conjugate Gradients
49 // convergence rate. Modern references for Conjugate Gradients are the
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| block_jacobi_preconditioner.h | 45 // conjugate gradients, or other iterative symmetric solvers. To use
50 // Before each use of the preconditioner in a solve with conjugate gradients,
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| /external/chromium_org/third_party/WebKit/Source/platform/audio/ |
| Biquad.h | 66 // Set the biquad coefficients given a single zero (other zero will be conjugate)
67 // and a single pole (other pole will be conjugate)
70 // Set the biquad coefficients given a single pole (other pole will be conjugate)
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| /external/eigen/unsupported/Eigen/ |
| IterativeSolvers | 19 * - a constrained conjugate gradient
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| /external/eigen/Eigen/src/Geometry/ |
| OrthoMethods.h | 111 res.row(0) = (_expression().row(1) * other.coeff(2) - _expression().row(2) * other.coeff(1)).conjugate();
112 res.row(1) = (_expression().row(2) * other.coeff(0) - _expression().row(0) * other.coeff(2)).conjugate();
113 res.row(2) = (_expression().row(0) * other.coeff(1) - _expression().row(1) * other.coeff(0)).conjugate();
118 res.col(0) = (_expression().col(1) * other.coeff(2) - _expression().col(2) * other.coeff(1)).conjugate();
119 res.col(1) = (_expression().col(2) * other.coeff(0) - _expression().col(0) * other.coeff(2)).conjugate();
120 res.col(2) = (_expression().col(0) * other.coeff(1) - _expression().col(1) * other.coeff(0)).conjugate();
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| /external/eigen/doc/ |
| C02_TutorialMatrixArithmetic.dox | 94 The transpose \f$ a^T \f$, conjugate \f$ \bar{a} \f$, and adjoint (i.e., conjugate transpose) \f$ a^* \f$ of a matrix or vector \f$ a \f$ are obtained by the member functions \link DenseBase::transpose() transpose()\endlink, \link MatrixBase::conjugate() conjugate()\endlink, and \link MatrixBase::adjoint() adjoint()\endlink, respectively.
105 For real matrices, \c conjugate() is a no-operation, and so \c adjoint() is equivalent to \c transpose().
175 When using complex numbers, Eigen's dot product is conjugate-linear in the first variable and linear in the
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