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various compilation and bug fixes in selfadjoint stuff
This commit is contained in:
Gael Guennebaud
parent
b5e4064289
commit
0590c18555
@ -125,20 +125,24 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView
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* The vectors \a u and \c v \b must be column vectors, however they can be
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* a adjoint expression without any overhead. Only the meaningful triangular
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* part of the matrix is updated, the rest is left unchanged.
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*
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* \sa rankUpdate(const MatrixBase<DerivedU>&, Scalar)
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*/
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template<typename DerivedU, typename DerivedV>
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SelfAdjointView& rank2update(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha = Scalar(1));
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SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha = Scalar(1));
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/** Perform a symmetric rank K update of the selfadjoint matrix \c *this:
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* \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix.
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*
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*
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* \returns a reference to \c *this
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*
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* Note that to perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply
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* call this function with u.adjoint().
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*
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* \sa rankUpdate(const MatrixBase<DerivedU>&, const MatrixBase<DerivedV>&, Scalar)
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*/
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template<typename DerivedU>
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SelfAdjointView& rankKupdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
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SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1));
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/////////// Cholesky module ///////////
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@ -231,13 +235,14 @@ struct ei_selfadjoint_product_returntype<Lhs,LhsMode,false,Rhs,0,true>
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template<typename Dest> void evalTo(Dest& dst) const
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{
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dst.resize(m_lhs.rows(), m_rhs.cols());
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dst.setZero();
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evalTo(dst,1);
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}
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template<typename Dest> void evalTo(Dest& dst, Scalar alpha) const
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{
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ei_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols());
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const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs);
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const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs);
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@ -63,9 +63,6 @@ static EIGEN_DONT_INLINE void ei_product_selfadjoint_vector(
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rhs = r;
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}
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for (int i=0;i<size;i++)
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res[i] = 0;
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int bound = std::max(0,size-8) & 0xfffffffE;
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if (FirstTriangular)
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bound = size - bound;
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@ -126,7 +126,7 @@ struct ei_selfadjoint_product<Scalar,MatStorageOrder, ColMajor, AAT, UpLo>
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template<typename MatrixType, unsigned int UpLo>
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template<typename DerivedU>
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SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
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::rankKupdate(const MatrixBase<DerivedU>& u, Scalar alpha)
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::rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha)
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{
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typedef ei_blas_traits<DerivedU> UBlasTraits;
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typedef typename UBlasTraits::DirectLinearAccessType ActualUType;
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@ -41,7 +41,7 @@ struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,LowerTriangular>
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// std::cerr << "lower \n" << u.transpose() << "\n" << v.transpose() << "\n\n";
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for (int i=0; i<size; ++i)
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{
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// std::cerr <<
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// std::cerr <<
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Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i+i, size-i) +=
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(alpha * ei_conj(u.coeff(i))) * v.end(size-i)
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+ (alpha * ei_conj(v.coeff(i))) * u.end(size-i);
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@ -70,13 +70,13 @@ template<bool Cond, typename T> struct ei_conj_expr_if
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template<typename MatrixType, unsigned int UpLo>
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template<typename DerivedU, typename DerivedV>
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SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
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::rank2update(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha)
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::rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha)
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{
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typedef ei_blas_traits<DerivedU> UBlasTraits;
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typedef typename UBlasTraits::DirectLinearAccessType ActualUType;
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typedef typename ei_cleantype<ActualUType>::type _ActualUType;
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const ActualUType actualU = UBlasTraits::extract(u.derived());
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typedef ei_blas_traits<DerivedV> VBlasTraits;
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typedef typename VBlasTraits::DirectLinearAccessType ActualVType;
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typedef typename ei_cleantype<ActualVType>::type _ActualVType;
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@ -87,8 +87,8 @@ SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo>
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enum { IsRowMajor = (ei_traits<MatrixType>::Flags&RowMajorBit)?1:0 };
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ei_selfadjoint_rank2_update_selector<Scalar,
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typename ei_conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::ret,
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typename ei_conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::ret,
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typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::ret>::type,
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typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::ret>::type,
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(IsRowMajor ? (UpLo==UpperTriangular ? LowerTriangular : UpperTriangular) : UpLo)>
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::run(const_cast<Scalar*>(_expression().data()),_expression().stride(),actualU,actualV,actualAlpha);
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@ -224,21 +224,19 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType&
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// Apply similarity transformation to remaining columns,
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// i.e., A = H' A H where H = I - h v v' and v = matA.col(i).end(n-i-1)
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matA.col(i).coeffRef(i+1) = 1;
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// hCoeffs.end(n-i-1) = (matA.corner(BottomRight,n-i-1,n-i-1).template part<LowerTriangular|SelfAdjoint>()
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// * matA.col(i).end(n-i-1)).lazy();
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// TODO map the above code to the function call below:
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ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,LowerTriangularBit>
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(n-i-1,matA.corner(BottomRight,n-i-1,n-i-1).data(), matA.stride(), matA.col(i).end(n-i-1).data(), const_cast<Scalar*>(hCoeffs.end(n-i-1).data()));
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// hCoeffs.end(n-i-1) = (matA.corner(BottomRight,n-i-1,n-i-1).template selfadjointView<LowerTriangular>()
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// * (h * matA.col(i).end(n-i-1)));
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hCoeffs.end(n-i-1) = hCoeffs.end(n-i-1)*h
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+ (h*ei_conj(h)*Scalar(-0.5)*(matA.col(i).end(n-i-1).dot(hCoeffs.end(n-i-1)))) *
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matA.col(i).end(n-i-1);
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hCoeffs.end(n-i-1).setZero();
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ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,LowerTriangular,false,false>
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(n-i-1,matA.corner(BottomRight,n-i-1,n-i-1).data(), matA.stride(), matA.col(i).end(n-i-1).data(), 1, const_cast<Scalar*>(hCoeffs.end(n-i-1).data()), h);
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hCoeffs.end(n-i-1) += (h*Scalar(-0.5)*(matA.col(i).end(n-i-1).dot(hCoeffs.end(n-i-1)))) * matA.col(i).end(n-i-1);
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matA.corner(BottomRight, n-i-1, n-i-1).template selfadjointView<LowerTriangular>()
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.rank2update(matA.col(i).end(n-i-1), hCoeffs.end(n-i-1), -1);
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.rankUpdate(matA.col(i).end(n-i-1), hCoeffs.end(n-i-1), -1);
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// note: at that point matA(i+1,i+1) is the (i+1)-th element of the final diagonal
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// note: the sequence of the beta values leads to the subdiagonal entries
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@ -119,8 +119,8 @@ void test_eigensolver_selfadjoint()
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// very important to test a 3x3 matrix since we provide a special path for it
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CALL_SUBTEST( selfadjointeigensolver(Matrix3f()) );
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CALL_SUBTEST( selfadjointeigensolver(Matrix4d()) );
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CALL_SUBTEST( selfadjointeigensolver(MatrixXf(4,4)) );
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CALL_SUBTEST( selfadjointeigensolver(MatrixXcd(7,7)) );
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CALL_SUBTEST( selfadjointeigensolver(MatrixXf(10,10)) );
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CALL_SUBTEST( selfadjointeigensolver(MatrixXcd(17,17)) );
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CALL_SUBTEST( selfadjointeigensolver(MatrixXd(19,19)) );
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// some trivial but implementation-wise tricky cases
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@ -62,13 +62,14 @@ template<typename MatrixType> void product_extra(const MatrixType& m)
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// all the expressions in this test should be compiled as a single matrix product
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// TODO: add internal checks to verify that
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VERIFY_IS_APPROX(m1 * m2.adjoint(), m1 * m2.adjoint().eval());
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VERIFY_IS_APPROX(m1.adjoint() * square.adjoint(), m1.adjoint().eval() * square.adjoint().eval());
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VERIFY_IS_APPROX(m1.adjoint() * m2, m1.adjoint().eval() * m2);
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VERIFY_IS_APPROX( (s1 * m1.adjoint()) * m2, (s1 * m1.adjoint()).eval() * m2);
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VERIFY_IS_APPROX( (- m1.adjoint() * s1) * (s3 * m2), (- m1.adjoint() * s1).eval() * (s3 * m2).eval());
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VERIFY_IS_APPROX( (s2 * m1.adjoint() * s1) * m2, (s2 * m1.adjoint() * s1).eval() * m2);
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VERIFY_IS_APPROX( (-m1*s2) * s1*m2.adjoint(), (-m1*s2).eval() * (s1*m2.adjoint()).eval());
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VERIFY_IS_APPROX(m3 = (m1 * m2.adjoint()).lazy(), m1 * m2.adjoint().eval());
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VERIFY_IS_APPROX(m3 = (m1.adjoint() * square.adjoint()).lazy(), m1.adjoint().eval() * square.adjoint().eval());
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VERIFY_IS_APPROX(m3 = (m1.adjoint() * m2).lazy(), m1.adjoint().eval() * m2);
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VERIFY_IS_APPROX(m3 = ((s1 * m1.adjoint()) * m2).lazy(), (s1 * m1.adjoint()).eval() * m2);
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VERIFY_IS_APPROX(m3 = ((- m1.adjoint() * s1) * (s3 * m2)).lazy(), (- m1.adjoint() * s1).eval() * (s3 * m2).eval());
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VERIFY_IS_APPROX(m3 = ((s2 * m1.adjoint() * s1) * m2).lazy(), (s2 * m1.adjoint() * s1).eval() * m2);
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VERIFY_IS_APPROX(m3 = ((-m1*s2) * s1*m2.adjoint()).lazy(), (-m1*s2).eval() * (s1*m2.adjoint()).eval());
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// a very tricky case where a scale factor has to be automatically conjugated:
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VERIFY_IS_APPROX( m1.adjoint() * (s1*m2).conjugate(), (m1.adjoint()).eval() * ((s1*m2).conjugate()).eval());
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@ -52,42 +52,23 @@ template<typename MatrixType> void product_selfadjoint(const MatrixType& m)
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m1 = (m1.adjoint() + m1).eval();
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// lower
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m2 = m1.template triangularView<LowerTriangular>();
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VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1) * (s2*v1));
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VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1.conjugate()) * (s2*v1));
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VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*m4.col(1)), (s1*m1) * (s2*m4.col(1)));
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VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*v1.conjugate()), (s1*m1) * (s2*v1.conjugate()));
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VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<LowerTriangular>() * (s2*v1.conjugate()), (s1*m1.conjugate()) * (s2*v1.conjugate()));
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// upper
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m2 = m1.template triangularView<UpperTriangular>();
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VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*v1), (s1*m1) * (s2*v1));
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VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<UpperTriangular>() * (s2*v1), (s1*m1.conjugate()) * (s2*v1));
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VERIFY_IS_APPROX(v3 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1.adjoint()) * (s2*v1));
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VERIFY_IS_APPROX(v3 = (s1*m2.transpose()).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1.transpose()) * (s2*v1));
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VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*v1.conjugate()), (s1*m1) * (s2*v1.conjugate()));
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VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<UpperTriangular>() * (s2*v1.conjugate()), (s1*m1.conjugate()) * (s2*v1.conjugate()));
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// rank2 update
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m2 = m1.template triangularView<LowerTriangular>();
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m2.template selfadjointView<LowerTriangular>().rank2update(v1,v2);
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m2.template selfadjointView<LowerTriangular>().rankUpdate(v1,v2);
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VERIFY_IS_APPROX(m2, (m1 + v1 * v2.adjoint()+ v2 * v1.adjoint()).template triangularView<LowerTriangular>().toDense());
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m2 = m1.template triangularView<UpperTriangular>();
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m2.template selfadjointView<UpperTriangular>().rank2update(-v1,s2*v2,s3);
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m2.template selfadjointView<UpperTriangular>().rankUpdate(-v1,s2*v2,s3);
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VERIFY_IS_APPROX(m2, (m1 + (-s2*s3) * (v1 * v2.adjoint()+ v2 * v1.adjoint())).template triangularView<UpperTriangular>().toDense());
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m2 = m1.template triangularView<UpperTriangular>();
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m2.template selfadjointView<UpperTriangular>().rank2update(-r1.adjoint(),r2.adjoint()*s3,s1);
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m2.template selfadjointView<UpperTriangular>().rankUpdate(-r1.adjoint(),r2.adjoint()*s3,s1);
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VERIFY_IS_APPROX(m2, (m1 + (-s3*s1) * (r1.adjoint() * r2 + r2.adjoint() * r1)).template triangularView<UpperTriangular>().toDense());
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if (rows>1)
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{
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m2 = m1.template triangularView<LowerTriangular>();
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m2.block(1,1,rows-1,cols-1).template selfadjointView<LowerTriangular>().rank2update(v1.end(rows-1),v2.start(cols-1));
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m2.block(1,1,rows-1,cols-1).template selfadjointView<LowerTriangular>().rankUpdate(v1.end(rows-1),v2.start(cols-1));
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m3 = m1;
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m3.block(1,1,rows-1,cols-1) += v1.end(rows-1) * v2.start(cols-1).adjoint()+ v2.start(cols-1) * v1.end(rows-1).adjoint();
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VERIFY_IS_APPROX(m2, m3.template triangularView<LowerTriangular>().toDense());
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@ -24,25 +24,43 @@
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#include "main.h"
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template<typename MatrixType> void symm(const MatrixType& m)
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{
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typedef typename MatrixType::Scalar Scalar;
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typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1;
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typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2;
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typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3;
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template<int OtherSize> struct symm_extra {
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template<typename M1, typename M2, typename Scalar>
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static void run(M1& m1, M1& m2, M2& rhs2, M2& rhs22, M2& rhs23, Scalar s1, Scalar s2)
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{
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m2 = m1.template triangularView<LowerTriangular>();
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VERIFY_IS_APPROX(rhs22 = (rhs2) * (m2).template selfadjointView<LowerTriangular>(),
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rhs23 = (rhs2) * (m1));
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VERIFY_IS_APPROX(rhs22 = (s2*rhs2) * (s1*m2).template selfadjointView<LowerTriangular>(),
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rhs23 = (s2*rhs2) * (s1*m1));
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}
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};
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int rows = m.rows();
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int cols = m.cols();
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template<> struct symm_extra<1> {
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template<typename M1, typename M2, typename Scalar>
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static void run(M1& m1, M1& m2, M2& rhs2, M2& rhs22, M2& rhs23, Scalar s1, Scalar s2) {}
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};
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template<typename Scalar, int Size, int OtherSize> void symm(int size = Size, int othersize = OtherSize)
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{
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typedef typename NumTraits<Scalar>::Real RealScalar;
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typedef Matrix<Scalar, Size, Size> MatrixType;
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typedef Matrix<Scalar, Size, OtherSize> Rhs1;
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typedef Matrix<Scalar, OtherSize, Size> Rhs2;
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typedef Matrix<Scalar, Size, OtherSize,RowMajor> Rhs3;
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int rows = size;
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int cols = size;
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MatrixType m1 = MatrixType::Random(rows, cols),
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m2 = MatrixType::Random(rows, cols);
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m1 = (m1+m1.adjoint()).eval();
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Rhs1 rhs1 = Rhs1::Random(cols, ei_random<int>(1,320)), rhs12, rhs13;
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Rhs2 rhs2 = Rhs2::Random(ei_random<int>(1,320), rows), rhs22, rhs23;
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Rhs3 rhs3 = Rhs3::Random(cols, ei_random<int>(1,320)), rhs32, rhs33;
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Rhs1 rhs1 = Rhs1::Random(cols, othersize), rhs12(cols, othersize), rhs13(cols, othersize);
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Rhs2 rhs2 = Rhs2::Random(othersize, rows), rhs22(othersize, rows), rhs23(othersize, rows);
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Rhs3 rhs3 = Rhs3::Random(cols, othersize), rhs32(cols, othersize), rhs33(cols, othersize);
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Scalar s1 = ei_random<Scalar>(),
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s2 = ei_random<Scalar>();
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@ -51,46 +69,44 @@ template<typename MatrixType> void symm(const MatrixType& m)
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VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs1),
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rhs13 = (s1*m1) * (s2*rhs1));
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m2 = m1.template triangularView<UpperTriangular>();
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VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs1),
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rhs13 = (s1*m1) * (s2*rhs1));
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m2 = m1.template triangularView<UpperTriangular>(); rhs12.setRandom(); rhs13 = rhs12;
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VERIFY_IS_APPROX(rhs12 += (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs1),
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rhs13 += (s1*m1) * (s2*rhs1));
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m2 = m1.template triangularView<LowerTriangular>();
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VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
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rhs23 = (s1*m1) * (s2*rhs2.adjoint()));
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VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
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rhs13 = (s1*m1) * (s2*rhs2.adjoint()));
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m2 = m1.template triangularView<UpperTriangular>();
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VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs2.adjoint()),
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rhs23 = (s1*m1) * (s2*rhs2.adjoint()));
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VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs2.adjoint()),
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rhs13 = (s1*m1) * (s2*rhs2.adjoint()));
|
||||
|
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m2 = m1.template triangularView<UpperTriangular>();
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VERIFY_IS_APPROX(rhs22 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
|
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rhs23 = (s1*m1.adjoint()) * (s2*rhs2.adjoint()));
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||||
VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()),
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rhs13 = (s1*m1.adjoint()) * (s2*rhs2.adjoint()));
|
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|
||||
// test row major = <...>
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m2 = m1.template triangularView<LowerTriangular>();
|
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VERIFY_IS_APPROX(rhs32 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs3),
|
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rhs33 = (s1*m1) * (s2 * rhs3));
|
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m2 = m1.template triangularView<LowerTriangular>(); rhs12.setRandom(); rhs13 = rhs12;
|
||||
VERIFY_IS_APPROX(rhs12 -= (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs3),
|
||||
rhs13 -= (s1*m1) * (s2 * rhs3));
|
||||
|
||||
m2 = m1.template triangularView<UpperTriangular>();
|
||||
VERIFY_IS_APPROX(rhs32 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs3).conjugate(),
|
||||
rhs33 = (s1*m1.adjoint()) * (s2*rhs3).conjugate());
|
||||
VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs3).conjugate(),
|
||||
rhs13 = (s1*m1.adjoint()) * (s2*rhs3).conjugate());
|
||||
|
||||
// test matrix * selfadjoint
|
||||
m2 = m1.template triangularView<LowerTriangular>();
|
||||
VERIFY_IS_APPROX(rhs22 = (rhs2) * (m2).template selfadjointView<LowerTriangular>(),
|
||||
rhs23 = (rhs2) * (m1));
|
||||
VERIFY_IS_APPROX(rhs22 = (s2*rhs2) * (s1*m2).template selfadjointView<LowerTriangular>(),
|
||||
rhs23 = (s2*rhs2) * (s1*m1));
|
||||
symm_extra<OtherSize>::run(m1,m2,rhs2,rhs22,rhs23,s1,s2);
|
||||
|
||||
}
|
||||
|
||||
void test_product_symm()
|
||||
{
|
||||
for(int i = 0; i < g_repeat ; i++)
|
||||
{
|
||||
int s;
|
||||
s = ei_random<int>(10,320);
|
||||
CALL_SUBTEST( symm(MatrixXf(s, s)) );
|
||||
s = ei_random<int>(10,320);
|
||||
CALL_SUBTEST( symm(MatrixXcd(s, s)) );
|
||||
CALL_SUBTEST(( symm<float,Dynamic,Dynamic>(ei_random<int>(10,320),ei_random<int>(10,320)) ));
|
||||
CALL_SUBTEST(( symm<std::complex<double>,Dynamic,Dynamic>(ei_random<int>(10,320),ei_random<int>(10,320)) ));
|
||||
|
||||
CALL_SUBTEST(( symm<float,Dynamic,1>(ei_random<int>(10,320)) ));
|
||||
CALL_SUBTEST(( symm<std::complex<double>,Dynamic,1>(ei_random<int>(10,320)) ));
|
||||
}
|
||||
}
|
||||
|
||||
@ -46,27 +46,27 @@ template<typename MatrixType> void syrk(const MatrixType& m)
|
||||
s2 = ei_random<Scalar>();
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX((m2.template selfadjointView<LowerTriangular>().rankKupdate(rhs2,s1)._expression()),
|
||||
VERIFY_IS_APPROX((m2.template selfadjointView<LowerTriangular>().rankUpdate(rhs2,s1)._expression()),
|
||||
((s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<LowerTriangular>().toDense()));
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankKupdate(rhs2,s1)._expression(),
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankUpdate(rhs2,s1)._expression(),
|
||||
(s1 * rhs2 * rhs2.adjoint()).eval().template triangularView<UpperTriangular>().toDense());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankKupdate(rhs1.adjoint(),s1)._expression(),
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankUpdate(rhs1.adjoint(),s1)._expression(),
|
||||
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<LowerTriangular>().toDense());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankKupdate(rhs1.adjoint(),s1)._expression(),
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankUpdate(rhs1.adjoint(),s1)._expression(),
|
||||
(s1 * rhs1.adjoint() * rhs1).eval().template triangularView<UpperTriangular>().toDense());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankKupdate(rhs3.adjoint(),s1)._expression(),
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<LowerTriangular>().rankUpdate(rhs3.adjoint(),s1)._expression(),
|
||||
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<LowerTriangular>().toDense());
|
||||
|
||||
m2.setZero();
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankKupdate(rhs3.adjoint(),s1)._expression(),
|
||||
VERIFY_IS_APPROX(m2.template selfadjointView<UpperTriangular>().rankUpdate(rhs3.adjoint(),s1)._expression(),
|
||||
(s1 * rhs3.adjoint() * rhs3).eval().template triangularView<UpperTriangular>().toDense());
|
||||
}
|
||||
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user