diff options
| -rw-r--r-- | Eigen/src/Core/SelfAdjointView.h | 13 | ||||
| -rw-r--r-- | Eigen/src/Core/products/SelfadjointMatrixVector.h | 3 | ||||
| -rw-r--r-- | Eigen/src/Core/products/SelfadjointProduct.h | 2 | ||||
| -rw-r--r-- | Eigen/src/Core/products/SelfadjointRank2Update.h | 10 | ||||
| -rw-r--r-- | Eigen/src/QR/Tridiagonalization.h | 18 | ||||
| -rw-r--r-- | test/eigensolver_selfadjoint.cpp | 4 | ||||
| -rw-r--r-- | test/product_extra.cpp | 15 | ||||
| -rw-r--r-- | test/product_selfadjoint.cpp | 27 | ||||
| -rw-r--r-- | test/product_symm.cpp | 84 | ||||
| -rw-r--r-- | test/product_syrk.cpp | 12 |
10 files changed, 93 insertions, 95 deletions
diff --git a/Eigen/src/Core/SelfAdjointView.h b/Eigen/src/Core/SelfAdjointView.h index 4787bcbd8..3faebfc5d 100644 --- a/Eigen/src/Core/SelfAdjointView.h +++ b/Eigen/src/Core/SelfAdjointView.h @@ -125,20 +125,24 @@ template<typename MatrixType, unsigned int UpLo> class SelfAdjointView * The vectors \a u and \c v \b must be column vectors, however they can be * a adjoint expression without any overhead. Only the meaningful triangular * part of the matrix is updated, the rest is left unchanged. + * + * \sa rankUpdate(const MatrixBase<DerivedU>&, Scalar) */ template<typename DerivedU, typename DerivedV> - SelfAdjointView& rank2update(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha = Scalar(1)); + SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha = Scalar(1)); /** Perform a symmetric rank K update of the selfadjoint matrix \c *this: * \f$ this = this + \alpha ( u u^* ) \f$ where \a u is a vector or matrix. - * + * * \returns a reference to \c *this * * Note that to perform \f$ this = this + \alpha ( u^* u ) \f$ you can simply * call this function with u.adjoint(). + * + * \sa rankUpdate(const MatrixBase<DerivedU>&, const MatrixBase<DerivedV>&, Scalar) */ template<typename DerivedU> - SelfAdjointView& rankKupdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1)); + SelfAdjointView& rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha = Scalar(1)); /////////// Cholesky module /////////// @@ -231,13 +235,14 @@ struct ei_selfadjoint_product_returntype<Lhs,LhsMode,false,Rhs,0,true> template<typename Dest> void evalTo(Dest& dst) const { - dst.resize(m_lhs.rows(), m_rhs.cols()); dst.setZero(); evalTo(dst,1); } template<typename Dest> void evalTo(Dest& dst, Scalar alpha) const { + ei_assert(dst.rows()==m_lhs.rows() && dst.cols()==m_rhs.cols()); + const ActualLhsType lhs = LhsBlasTraits::extract(m_lhs); const ActualRhsType rhs = RhsBlasTraits::extract(m_rhs); diff --git a/Eigen/src/Core/products/SelfadjointMatrixVector.h b/Eigen/src/Core/products/SelfadjointMatrixVector.h index 8e0dc9526..279836f8a 100644 --- a/Eigen/src/Core/products/SelfadjointMatrixVector.h +++ b/Eigen/src/Core/products/SelfadjointMatrixVector.h @@ -63,9 +63,6 @@ static EIGEN_DONT_INLINE void ei_product_selfadjoint_vector( rhs = r; } - for (int i=0;i<size;i++) - res[i] = 0; - int bound = std::max(0,size-8) & 0xfffffffE; if (FirstTriangular) bound = size - bound; diff --git a/Eigen/src/Core/products/SelfadjointProduct.h b/Eigen/src/Core/products/SelfadjointProduct.h index d971720d6..f6420d10c 100644 --- a/Eigen/src/Core/products/SelfadjointProduct.h +++ b/Eigen/src/Core/products/SelfadjointProduct.h @@ -126,7 +126,7 @@ struct ei_selfadjoint_product<Scalar,MatStorageOrder, ColMajor, AAT, UpLo> template<typename MatrixType, unsigned int UpLo> template<typename DerivedU> SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo> -::rankKupdate(const MatrixBase<DerivedU>& u, Scalar alpha) +::rankUpdate(const MatrixBase<DerivedU>& u, Scalar alpha) { typedef ei_blas_traits<DerivedU> UBlasTraits; typedef typename UBlasTraits::DirectLinearAccessType ActualUType; diff --git a/Eigen/src/Core/products/SelfadjointRank2Update.h b/Eigen/src/Core/products/SelfadjointRank2Update.h index 65a321fde..f7dcc003f 100644 --- a/Eigen/src/Core/products/SelfadjointRank2Update.h +++ b/Eigen/src/Core/products/SelfadjointRank2Update.h @@ -41,7 +41,7 @@ struct ei_selfadjoint_rank2_update_selector<Scalar,UType,VType,LowerTriangular> // std::cerr << "lower \n" << u.transpose() << "\n" << v.transpose() << "\n\n"; for (int i=0; i<size; ++i) { -// std::cerr << +// std::cerr << Map<Matrix<Scalar,Dynamic,1> >(mat+stride*i+i, size-i) += (alpha * ei_conj(u.coeff(i))) * v.end(size-i) + (alpha * ei_conj(v.coeff(i))) * u.end(size-i); @@ -70,13 +70,13 @@ template<bool Cond, typename T> struct ei_conj_expr_if template<typename MatrixType, unsigned int UpLo> template<typename DerivedU, typename DerivedV> SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo> -::rank2update(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha) +::rankUpdate(const MatrixBase<DerivedU>& u, const MatrixBase<DerivedV>& v, Scalar alpha) { typedef ei_blas_traits<DerivedU> UBlasTraits; typedef typename UBlasTraits::DirectLinearAccessType ActualUType; typedef typename ei_cleantype<ActualUType>::type _ActualUType; const ActualUType actualU = UBlasTraits::extract(u.derived()); - + typedef ei_blas_traits<DerivedV> VBlasTraits; typedef typename VBlasTraits::DirectLinearAccessType ActualVType; typedef typename ei_cleantype<ActualVType>::type _ActualVType; @@ -87,8 +87,8 @@ SelfAdjointView<MatrixType,UpLo>& SelfAdjointView<MatrixType,UpLo> enum { IsRowMajor = (ei_traits<MatrixType>::Flags&RowMajorBit)?1:0 }; ei_selfadjoint_rank2_update_selector<Scalar, - typename ei_conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::ret, - typename ei_conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::ret, + typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ UBlasTraits::NeedToConjugate,_ActualUType>::ret>::type, + typename ei_cleantype<typename ei_conj_expr_if<IsRowMajor ^ VBlasTraits::NeedToConjugate,_ActualVType>::ret>::type, (IsRowMajor ? (UpLo==UpperTriangular ? LowerTriangular : UpperTriangular) : UpLo)> ::run(const_cast<Scalar*>(_expression().data()),_expression().stride(),actualU,actualV,actualAlpha); diff --git a/Eigen/src/QR/Tridiagonalization.h b/Eigen/src/QR/Tridiagonalization.h index cf737bd30..a003fd59a 100644 --- a/Eigen/src/QR/Tridiagonalization.h +++ b/Eigen/src/QR/Tridiagonalization.h @@ -224,21 +224,19 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& // Apply similarity transformation to remaining columns, // i.e., A = H' A H where H = I - h v v' and v = matA.col(i).end(n-i-1) - matA.col(i).coeffRef(i+1) = 1; - // hCoeffs.end(n-i-1) = (matA.corner(BottomRight,n-i-1,n-i-1).template part<LowerTriangular|SelfAdjoint>() - // * matA.col(i).end(n-i-1)).lazy(); - // TODO map the above code to the function call below: - ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,LowerTriangularBit> - (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())); +// hCoeffs.end(n-i-1) = (matA.corner(BottomRight,n-i-1,n-i-1).template selfadjointView<LowerTriangular>() +// * (h * matA.col(i).end(n-i-1))); + + hCoeffs.end(n-i-1).setZero(); + ei_product_selfadjoint_vector<Scalar,MatrixType::Flags&RowMajorBit,LowerTriangular,false,false> + (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); - hCoeffs.end(n-i-1) = hCoeffs.end(n-i-1)*h - + (h*ei_conj(h)*Scalar(-0.5)*(matA.col(i).end(n-i-1).dot(hCoeffs.end(n-i-1)))) * - matA.col(i).end(n-i-1); + 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); matA.corner(BottomRight, n-i-1, n-i-1).template selfadjointView<LowerTriangular>() - .rank2update(matA.col(i).end(n-i-1), hCoeffs.end(n-i-1), -1); + .rankUpdate(matA.col(i).end(n-i-1), hCoeffs.end(n-i-1), -1); // note: at that point matA(i+1,i+1) is the (i+1)-th element of the final diagonal // note: the sequence of the beta values leads to the subdiagonal entries diff --git a/test/eigensolver_selfadjoint.cpp b/test/eigensolver_selfadjoint.cpp index 6b5092775..1f10b131b 100644 --- a/test/eigensolver_selfadjoint.cpp +++ b/test/eigensolver_selfadjoint.cpp @@ -119,8 +119,8 @@ void test_eigensolver_selfadjoint() // very important to test a 3x3 matrix since we provide a special path for it CALL_SUBTEST( selfadjointeigensolver(Matrix3f()) ); CALL_SUBTEST( selfadjointeigensolver(Matrix4d()) ); - CALL_SUBTEST( selfadjointeigensolver(MatrixXf(4,4)) ); - CALL_SUBTEST( selfadjointeigensolver(MatrixXcd(7,7)) ); + CALL_SUBTEST( selfadjointeigensolver(MatrixXf(10,10)) ); + CALL_SUBTEST( selfadjointeigensolver(MatrixXcd(17,17)) ); CALL_SUBTEST( selfadjointeigensolver(MatrixXd(19,19)) ); // some trivial but implementation-wise tricky cases diff --git a/test/product_extra.cpp b/test/product_extra.cpp index e750be65e..213dbced6 100644 --- a/test/product_extra.cpp +++ b/test/product_extra.cpp @@ -62,13 +62,14 @@ template<typename MatrixType> void product_extra(const MatrixType& m) // all the expressions in this test should be compiled as a single matrix product // TODO: add internal checks to verify that - VERIFY_IS_APPROX(m1 * m2.adjoint(), m1 * m2.adjoint().eval()); - VERIFY_IS_APPROX(m1.adjoint() * square.adjoint(), m1.adjoint().eval() * square.adjoint().eval()); - VERIFY_IS_APPROX(m1.adjoint() * m2, m1.adjoint().eval() * m2); - VERIFY_IS_APPROX( (s1 * m1.adjoint()) * m2, (s1 * m1.adjoint()).eval() * m2); - VERIFY_IS_APPROX( (- m1.adjoint() * s1) * (s3 * m2), (- m1.adjoint() * s1).eval() * (s3 * m2).eval()); - VERIFY_IS_APPROX( (s2 * m1.adjoint() * s1) * m2, (s2 * m1.adjoint() * s1).eval() * m2); - VERIFY_IS_APPROX( (-m1*s2) * s1*m2.adjoint(), (-m1*s2).eval() * (s1*m2.adjoint()).eval()); + VERIFY_IS_APPROX(m3 = (m1 * m2.adjoint()).lazy(), m1 * m2.adjoint().eval()); + VERIFY_IS_APPROX(m3 = (m1.adjoint() * square.adjoint()).lazy(), m1.adjoint().eval() * square.adjoint().eval()); + VERIFY_IS_APPROX(m3 = (m1.adjoint() * m2).lazy(), m1.adjoint().eval() * m2); + VERIFY_IS_APPROX(m3 = ((s1 * m1.adjoint()) * m2).lazy(), (s1 * m1.adjoint()).eval() * m2); + VERIFY_IS_APPROX(m3 = ((- m1.adjoint() * s1) * (s3 * m2)).lazy(), (- m1.adjoint() * s1).eval() * (s3 * m2).eval()); + VERIFY_IS_APPROX(m3 = ((s2 * m1.adjoint() * s1) * m2).lazy(), (s2 * m1.adjoint() * s1).eval() * m2); + VERIFY_IS_APPROX(m3 = ((-m1*s2) * s1*m2.adjoint()).lazy(), (-m1*s2).eval() * (s1*m2.adjoint()).eval()); + // a very tricky case where a scale factor has to be automatically conjugated: VERIFY_IS_APPROX( m1.adjoint() * (s1*m2).conjugate(), (m1.adjoint()).eval() * ((s1*m2).conjugate()).eval()); diff --git a/test/product_selfadjoint.cpp b/test/product_selfadjoint.cpp index efa487ab1..e47358197 100644 --- a/test/product_selfadjoint.cpp +++ b/test/product_selfadjoint.cpp @@ -52,42 +52,23 @@ template<typename MatrixType> void product_selfadjoint(const MatrixType& m) m1 = (m1.adjoint() + m1).eval(); - // lower - m2 = m1.template triangularView<LowerTriangular>(); - VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1) * (s2*v1)); - VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1.conjugate()) * (s2*v1)); - VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*m4.col(1)), (s1*m1) * (s2*m4.col(1))); - - VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*v1.conjugate()), (s1*m1) * (s2*v1.conjugate())); - VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<LowerTriangular>() * (s2*v1.conjugate()), (s1*m1.conjugate()) * (s2*v1.conjugate())); - - // upper - m2 = m1.template triangularView<UpperTriangular>(); - VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*v1), (s1*m1) * (s2*v1)); - VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<UpperTriangular>() * (s2*v1), (s1*m1.conjugate()) * (s2*v1)); - VERIFY_IS_APPROX(v3 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1.adjoint()) * (s2*v1)); - VERIFY_IS_APPROX(v3 = (s1*m2.transpose()).template selfadjointView<LowerTriangular>() * (s2*v1), (s1*m1.transpose()) * (s2*v1)); - - VERIFY_IS_APPROX(v3 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*v1.conjugate()), (s1*m1) * (s2*v1.conjugate())); - VERIFY_IS_APPROX(v3 = (s1*m2.conjugate()).template selfadjointView<UpperTriangular>() * (s2*v1.conjugate()), (s1*m1.conjugate()) * (s2*v1.conjugate())); - // rank2 update m2 = m1.template triangularView<LowerTriangular>(); - m2.template selfadjointView<LowerTriangular>().rank2update(v1,v2); + m2.template selfadjointView<LowerTriangular>().rankUpdate(v1,v2); VERIFY_IS_APPROX(m2, (m1 + v1 * v2.adjoint()+ v2 * v1.adjoint()).template triangularView<LowerTriangular>().toDense()); m2 = m1.template triangularView<UpperTriangular>(); - m2.template selfadjointView<UpperTriangular>().rank2update(-v1,s2*v2,s3); + m2.template selfadjointView<UpperTriangular>().rankUpdate(-v1,s2*v2,s3); VERIFY_IS_APPROX(m2, (m1 + (-s2*s3) * (v1 * v2.adjoint()+ v2 * v1.adjoint())).template triangularView<UpperTriangular>().toDense()); m2 = m1.template triangularView<UpperTriangular>(); - m2.template selfadjointView<UpperTriangular>().rank2update(-r1.adjoint(),r2.adjoint()*s3,s1); + m2.template selfadjointView<UpperTriangular>().rankUpdate(-r1.adjoint(),r2.adjoint()*s3,s1); VERIFY_IS_APPROX(m2, (m1 + (-s3*s1) * (r1.adjoint() * r2 + r2.adjoint() * r1)).template triangularView<UpperTriangular>().toDense()); if (rows>1) { m2 = m1.template triangularView<LowerTriangular>(); - m2.block(1,1,rows-1,cols-1).template selfadjointView<LowerTriangular>().rank2update(v1.end(rows-1),v2.start(cols-1)); + m2.block(1,1,rows-1,cols-1).template selfadjointView<LowerTriangular>().rankUpdate(v1.end(rows-1),v2.start(cols-1)); m3 = m1; 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(); VERIFY_IS_APPROX(m2, m3.template triangularView<LowerTriangular>().toDense()); diff --git a/test/product_symm.cpp b/test/product_symm.cpp index 3a0cd94d0..54bf91fb9 100644 --- a/test/product_symm.cpp +++ b/test/product_symm.cpp @@ -24,25 +24,43 @@ #include "main.h" -template<typename MatrixType> void symm(const MatrixType& m) +template<int OtherSize> struct symm_extra { + template<typename M1, typename M2, typename Scalar> + static void run(M1& m1, M1& m2, M2& rhs2, M2& rhs22, M2& rhs23, Scalar s1, Scalar s2) + { + 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)); + } +}; + +template<> struct symm_extra<1> { + template<typename M1, typename M2, typename Scalar> + static void run(M1& m1, M1& m2, M2& rhs2, M2& rhs22, M2& rhs23, Scalar s1, Scalar s2) {} +}; + +template<typename Scalar, int Size, int OtherSize> void symm(int size = Size, int othersize = OtherSize) { - typedef typename MatrixType::Scalar Scalar; typedef typename NumTraits<Scalar>::Real RealScalar; - typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic> Rhs1; - typedef Matrix<Scalar, Dynamic, MatrixType::RowsAtCompileTime> Rhs2; - typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, Dynamic,RowMajor> Rhs3; - int rows = m.rows(); - int cols = m.cols(); + typedef Matrix<Scalar, Size, Size> MatrixType; + typedef Matrix<Scalar, Size, OtherSize> Rhs1; + typedef Matrix<Scalar, OtherSize, Size> Rhs2; + typedef Matrix<Scalar, Size, OtherSize,RowMajor> Rhs3; + + int rows = size; + int cols = size; MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols); m1 = (m1+m1.adjoint()).eval(); - Rhs1 rhs1 = Rhs1::Random(cols, ei_random<int>(1,320)), rhs12, rhs13; - Rhs2 rhs2 = Rhs2::Random(ei_random<int>(1,320), rows), rhs22, rhs23; - Rhs3 rhs3 = Rhs3::Random(cols, ei_random<int>(1,320)), rhs32, rhs33; + Rhs1 rhs1 = Rhs1::Random(cols, othersize), rhs12(cols, othersize), rhs13(cols, othersize); + Rhs2 rhs2 = Rhs2::Random(othersize, rows), rhs22(othersize, rows), rhs23(othersize, rows); + Rhs3 rhs3 = Rhs3::Random(cols, othersize), rhs32(cols, othersize), rhs33(cols, othersize); Scalar s1 = ei_random<Scalar>(), s2 = ei_random<Scalar>(); @@ -51,46 +69,44 @@ template<typename MatrixType> void symm(const MatrixType& m) VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs1), rhs13 = (s1*m1) * (s2*rhs1)); - m2 = m1.template triangularView<UpperTriangular>(); - VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs1), - rhs13 = (s1*m1) * (s2*rhs1)); + m2 = m1.template triangularView<UpperTriangular>(); rhs12.setRandom(); rhs13 = rhs12; + VERIFY_IS_APPROX(rhs12 += (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs1), + rhs13 += (s1*m1) * (s2*rhs1)); m2 = m1.template triangularView<LowerTriangular>(); - VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()), - rhs23 = (s1*m1) * (s2*rhs2.adjoint())); + VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()), + rhs13 = (s1*m1) * (s2*rhs2.adjoint())); m2 = m1.template triangularView<UpperTriangular>(); - VERIFY_IS_APPROX(rhs22 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs2.adjoint()), - rhs23 = (s1*m1) * (s2*rhs2.adjoint())); + VERIFY_IS_APPROX(rhs12 = (s1*m2).template selfadjointView<UpperTriangular>() * (s2*rhs2.adjoint()), + rhs13 = (s1*m1) * (s2*rhs2.adjoint())); m2 = m1.template triangularView<UpperTriangular>(); - VERIFY_IS_APPROX(rhs22 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()), - rhs23 = (s1*m1.adjoint()) * (s2*rhs2.adjoint())); + VERIFY_IS_APPROX(rhs12 = (s1*m2.adjoint()).template selfadjointView<LowerTriangular>() * (s2*rhs2.adjoint()), + rhs13 = (s1*m1.adjoint()) * (s2*rhs2.adjoint())); // test row major = <...> - m2 = m1.template triangularView<LowerTriangular>(); - VERIFY_IS_APPROX(rhs32 = (s1*m2).template selfadjointView<LowerTriangular>() * (s2*rhs3), - rhs33 = (s1*m1) * (s2 * rhs3)); + 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)) )); } } diff --git a/test/product_syrk.cpp b/test/product_syrk.cpp index ff8bf933d..be0606c96 100644 --- a/test/product_syrk.cpp +++ b/test/product_syrk.cpp @@ -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()); } |