diff options
Diffstat (limited to 'test')
| -rw-r--r-- | test/cholesky.cpp | 64 | ||||
| -rw-r--r-- | test/lu.cpp | 23 | ||||
| -rw-r--r-- | test/main.h | 16 | ||||
| -rw-r--r-- | test/mixingtypes.cpp | 8 | ||||
| -rw-r--r-- | test/product_large.cpp | 2 | ||||
| -rw-r--r-- | test/rand.cpp | 3 | ||||
| -rw-r--r-- | test/svd_fill.h | 12 | ||||
| -rw-r--r-- | test/swap.cpp | 11 | ||||
| -rw-r--r-- | test/vectorization_logic.cpp | 49 |
9 files changed, 151 insertions, 37 deletions
diff --git a/test/cholesky.cpp b/test/cholesky.cpp index d652af5bf..b7abc230b 100644 --- a/test/cholesky.cpp +++ b/test/cholesky.cpp @@ -17,6 +17,12 @@ #include <Eigen/Cholesky> #include <Eigen/QR> +template<typename MatrixType, int UpLo> +typename MatrixType::RealScalar matrix_l1_norm(const MatrixType& m) { + MatrixType symm = m.template selfadjointView<UpLo>(); + return symm.cwiseAbs().colwise().sum().maxCoeff(); +} + template<typename MatrixType,template <typename,int> class CholType> void test_chol_update(const MatrixType& symm) { typedef typename MatrixType::Scalar Scalar; @@ -77,7 +83,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m) { SquareMatrixType symmUp = symm.template triangularView<Upper>(); SquareMatrixType symmLo = symm.template triangularView<Lower>(); - + LLT<SquareMatrixType,Lower> chollo(symmLo); VERIFY_IS_APPROX(symm, chollo.reconstructedMatrix()); vecX = chollo.solve(vecB); @@ -85,6 +91,14 @@ template<typename MatrixType> void cholesky(const MatrixType& m) matX = chollo.solve(matB); VERIFY_IS_APPROX(symm * matX, matB); + const MatrixType symmLo_inverse = chollo.solve(MatrixType::Identity(rows,cols)); + RealScalar rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Lower>(symmLo)) / + matrix_l1_norm<MatrixType, Lower>(symmLo_inverse); + RealScalar rcond_est = chollo.rcond(); + // Verify that the estimated condition number is within a factor of 10 of the + // truth. + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); + // test the upper mode LLT<SquareMatrixType,Upper> cholup(symmUp); VERIFY_IS_APPROX(symm, cholup.reconstructedMatrix()); @@ -93,6 +107,15 @@ template<typename MatrixType> void cholesky(const MatrixType& m) matX = cholup.solve(matB); VERIFY_IS_APPROX(symm * matX, matB); + // Verify that the estimated condition number is within a factor of 10 of the + // truth. + const MatrixType symmUp_inverse = cholup.solve(MatrixType::Identity(rows,cols)); + rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Upper>(symmUp)) / + matrix_l1_norm<MatrixType, Upper>(symmUp_inverse); + rcond_est = cholup.rcond(); + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); + + MatrixType neg = -symmLo; chollo.compute(neg); VERIFY(chollo.info()==NumericalIssue); @@ -101,7 +124,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m) VERIFY_IS_APPROX(MatrixType(chollo.matrixU().transpose().conjugate()), MatrixType(chollo.matrixL())); VERIFY_IS_APPROX(MatrixType(cholup.matrixL().transpose().conjugate()), MatrixType(cholup.matrixU())); VERIFY_IS_APPROX(MatrixType(cholup.matrixU().transpose().conjugate()), MatrixType(cholup.matrixL())); - + // test some special use cases of SelfCwiseBinaryOp: MatrixType m1 = MatrixType::Random(rows,cols), m2(rows,cols); m2 = m1; @@ -137,6 +160,15 @@ template<typename MatrixType> void cholesky(const MatrixType& m) matX = ldltlo.solve(matB); VERIFY_IS_APPROX(symm * matX, matB); + const MatrixType symmLo_inverse = ldltlo.solve(MatrixType::Identity(rows,cols)); + RealScalar rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Lower>(symmLo)) / + matrix_l1_norm<MatrixType, Lower>(symmLo_inverse); + RealScalar rcond_est = ldltlo.rcond(); + // Verify that the estimated condition number is within a factor of 10 of the + // truth. + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); + + LDLT<SquareMatrixType,Upper> ldltup(symmUp); VERIFY_IS_APPROX(symm, ldltup.reconstructedMatrix()); vecX = ldltup.solve(vecB); @@ -144,6 +176,14 @@ template<typename MatrixType> void cholesky(const MatrixType& m) matX = ldltup.solve(matB); VERIFY_IS_APPROX(symm * matX, matB); + // Verify that the estimated condition number is within a factor of 10 of the + // truth. + const MatrixType symmUp_inverse = ldltup.solve(MatrixType::Identity(rows,cols)); + rcond = (RealScalar(1) / matrix_l1_norm<MatrixType, Upper>(symmUp)) / + matrix_l1_norm<MatrixType, Upper>(symmUp_inverse); + rcond_est = ldltup.rcond(); + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); + VERIFY_IS_APPROX(MatrixType(ldltlo.matrixL().transpose().conjugate()), MatrixType(ldltlo.matrixU())); VERIFY_IS_APPROX(MatrixType(ldltlo.matrixU().transpose().conjugate()), MatrixType(ldltlo.matrixL())); VERIFY_IS_APPROX(MatrixType(ldltup.matrixL().transpose().conjugate()), MatrixType(ldltup.matrixU())); @@ -167,7 +207,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m) // restore if(sign == -1) symm = -symm; - + // check matrices coming from linear constraints with Lagrange multipliers if(rows>=3) { @@ -183,7 +223,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m) vecX = ldltlo.solve(vecB); VERIFY_IS_APPROX(A * vecX, vecB); } - + // check non-full rank matrices if(rows>=3) { @@ -199,7 +239,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m) vecX = ldltlo.solve(vecB); VERIFY_IS_APPROX(A * vecX, vecB); } - + // check matrices with a wide spectrum if(rows>=3) { @@ -225,7 +265,7 @@ template<typename MatrixType> void cholesky(const MatrixType& m) { RealScalar large_tol = std::sqrt(test_precision<RealScalar>()); VERIFY((A * vecX).isApprox(vecB, large_tol)); - + ++g_test_level; VERIFY_IS_APPROX(A * vecX,vecB); --g_test_level; @@ -314,14 +354,14 @@ template<typename MatrixType> void cholesky_bug241(const MatrixType& m) } // LDLT is not guaranteed to work for indefinite matrices, but happens to work fine if matrix is diagonal. -// This test checks that LDLT reports correctly that matrix is indefinite. +// This test checks that LDLT reports correctly that matrix is indefinite. // See http://forum.kde.org/viewtopic.php?f=74&t=106942 and bug 736 template<typename MatrixType> void cholesky_definiteness(const MatrixType& m) { eigen_assert(m.rows() == 2 && m.cols() == 2); MatrixType mat; LDLT<MatrixType> ldlt(2); - + { mat << 1, 0, 0, -1; ldlt.compute(mat); @@ -384,11 +424,11 @@ void test_cholesky() CALL_SUBTEST_3( cholesky_definiteness(Matrix2d()) ); CALL_SUBTEST_4( cholesky(Matrix3f()) ); CALL_SUBTEST_5( cholesky(Matrix4d()) ); - - s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE); + + s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE); CALL_SUBTEST_2( cholesky(MatrixXd(s,s)) ); TEST_SET_BUT_UNUSED_VARIABLE(s) - + s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/2); CALL_SUBTEST_6( cholesky_cplx(MatrixXcd(s,s)) ); TEST_SET_BUT_UNUSED_VARIABLE(s) @@ -402,6 +442,6 @@ void test_cholesky() // Test problem size constructors CALL_SUBTEST_9( LLT<MatrixXf>(10) ); CALL_SUBTEST_9( LDLT<MatrixXf>(10) ); - + TEST_SET_BUT_UNUSED_VARIABLE(nb_temporaries) } diff --git a/test/lu.cpp b/test/lu.cpp index f14435114..9787f4d86 100644 --- a/test/lu.cpp +++ b/test/lu.cpp @@ -11,6 +11,11 @@ #include <Eigen/LU> using namespace std; +template<typename MatrixType> +typename MatrixType::RealScalar matrix_l1_norm(const MatrixType& m) { + return m.cwiseAbs().colwise().sum().maxCoeff(); +} + template<typename MatrixType> void lu_non_invertible() { typedef typename MatrixType::Index Index; @@ -143,7 +148,14 @@ template<typename MatrixType> void lu_invertible() m3 = MatrixType::Random(size,size); m2 = lu.solve(m3); VERIFY_IS_APPROX(m3, m1*m2); - VERIFY_IS_APPROX(m2, lu.inverse()*m3); + MatrixType m1_inverse = lu.inverse(); + VERIFY_IS_APPROX(m2, m1_inverse*m3); + + RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse); + const RealScalar rcond_est = lu.rcond(); + // Verify that the estimated condition number is within a factor of 10 of the + // truth. + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); // test solve with transposed lu.template _solve_impl_transposed<false>(m3, m2); @@ -170,6 +182,7 @@ template<typename MatrixType> void lu_partial_piv() PartialPivLU.h */ typedef typename MatrixType::Index Index; + typedef typename NumTraits<typename MatrixType::Scalar>::Real RealScalar; Index size = internal::random<Index>(1,4); MatrixType m1(size, size), m2(size, size), m3(size, size); @@ -181,7 +194,13 @@ template<typename MatrixType> void lu_partial_piv() m3 = MatrixType::Random(size,size); m2 = plu.solve(m3); VERIFY_IS_APPROX(m3, m1*m2); - VERIFY_IS_APPROX(m2, plu.inverse()*m3); + MatrixType m1_inverse = plu.inverse(); + VERIFY_IS_APPROX(m2, m1_inverse*m3); + + RealScalar rcond = (RealScalar(1) / matrix_l1_norm(m1)) / matrix_l1_norm(m1_inverse); + const RealScalar rcond_est = plu.rcond(); + // Verify that the estimate is within a factor of 10 of the truth. + VERIFY(rcond_est > rcond / 10 && rcond_est < rcond * 10); // test solve with transposed plu.template _solve_impl_transposed<false>(m3, m2); diff --git a/test/main.h b/test/main.h index bba5e7570..b0e3b7818 100644 --- a/test/main.h +++ b/test/main.h @@ -275,6 +275,10 @@ inline void verify_impl(bool condition, const char *testname, const char *file, #define VERIFY(a) ::verify_impl(a, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a)) +#define VERIFY_GE(a, b) ::verify_impl(a >= b, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a >= b)) +#define VERIFY_LE(a, b) ::verify_impl(a <= b, g_test_stack.back().c_str(), __FILE__, __LINE__, EI_PP_MAKE_STRING(a <= b)) + + #define VERIFY_IS_EQUAL(a, b) VERIFY(test_is_equal(a, b)) #define VERIFY_IS_NOT_EQUAL(a, b) VERIFY(!test_is_equal(a, b)) #define VERIFY_IS_APPROX(a, b) VERIFY(verifyIsApprox(a, b)) @@ -316,9 +320,9 @@ inline bool test_isMuchSmallerThan(const float& a, const float& b) { return internal::isMuchSmallerThan(a, b, test_precision<float>()); } inline bool test_isApproxOrLessThan(const float& a, const float& b) { return internal::isApproxOrLessThan(a, b, test_precision<float>()); } + inline bool test_isApprox(const double& a, const double& b) { return internal::isApprox(a, b, test_precision<double>()); } - inline bool test_isMuchSmallerThan(const double& a, const double& b) { return internal::isMuchSmallerThan(a, b, test_precision<double>()); } inline bool test_isApproxOrLessThan(const double& a, const double& b) @@ -359,6 +363,12 @@ inline bool test_isApproxOrLessThan(const long double& a, const long double& b) { return internal::isApproxOrLessThan(a, b, test_precision<long double>()); } #endif // EIGEN_TEST_NO_LONGDOUBLE +inline bool test_isApprox(const half& a, const half& b) +{ return internal::isApprox(a, b, test_precision<half>()); } +inline bool test_isMuchSmallerThan(const half& a, const half& b) +{ return internal::isMuchSmallerThan(a, b, test_precision<half>()); } +inline bool test_isApproxOrLessThan(const half& a, const half& b) +{ return internal::isApproxOrLessThan(a, b, test_precision<half>()); } // test_relative_error returns the relative difference between a and b as a real scalar as used in isApprox. template<typename T1,typename T2> @@ -426,9 +436,7 @@ template<typename T1,typename T2> typename NumTraits<T1>::Real test_relative_error(const T1 &a, const T2 &b, typename internal::enable_if<internal::is_arithmetic<typename NumTraits<T1>::Real>::value, T1>::type* = 0) { typedef typename NumTraits<T1>::Real RealScalar; - using std::min; - using std::sqrt; - return sqrt(RealScalar(numext::abs2(a-b))/RealScalar((min)(numext::abs2(a),numext::abs2(b)))); + return numext::sqrt(RealScalar(numext::abs2(a-b))/RealScalar((numext::mini)(numext::abs2(a),numext::abs2(b)))); } template<typename T> diff --git a/test/mixingtypes.cpp b/test/mixingtypes.cpp index a3b469af8..0b381ec6c 100644 --- a/test/mixingtypes.cpp +++ b/test/mixingtypes.cpp @@ -148,10 +148,14 @@ template<int SizeAtCompileType> void mixingtypes(int size = SizeAtCompileType) VERIFY_IS_APPROX(sd*vd.adjoint()*mcd, sd*vd.adjoint().template cast<CD>().eval()*mcd); VERIFY_IS_APPROX(scd*vd.adjoint()*mcd, scd*vd.adjoint().template cast<CD>().eval()*mcd); - VERIFY_IS_APPROX(sd*vcd.adjoint()*md.template triangularView<Upper>(), sd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Upper>()); + VERIFY_IS_APPROX( sd*vcd.adjoint()*md.template triangularView<Upper>(), sd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Upper>()); VERIFY_IS_APPROX(scd*vcd.adjoint()*md.template triangularView<Lower>(), scd*vcd.adjoint()*md.template cast<CD>().eval().template triangularView<Lower>()); - VERIFY_IS_APPROX(sd*vd.adjoint()*mcd.template triangularView<Lower>(), sd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Lower>()); + VERIFY_IS_APPROX( sd*vcd.adjoint()*md.transpose().template triangularView<Upper>(), sd*vcd.adjoint()*md.transpose().template cast<CD>().eval().template triangularView<Upper>()); + VERIFY_IS_APPROX(scd*vcd.adjoint()*md.transpose().template triangularView<Lower>(), scd*vcd.adjoint()*md.transpose().template cast<CD>().eval().template triangularView<Lower>()); + VERIFY_IS_APPROX( sd*vd.adjoint()*mcd.template triangularView<Lower>(), sd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Lower>()); VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.template triangularView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.template triangularView<Upper>()); + VERIFY_IS_APPROX( sd*vd.adjoint()*mcd.transpose().template triangularView<Lower>(), sd*vd.adjoint().template cast<CD>().eval()*mcd.transpose().template triangularView<Lower>()); + VERIFY_IS_APPROX(scd*vd.adjoint()*mcd.transpose().template triangularView<Upper>(), scd*vd.adjoint().template cast<CD>().eval()*mcd.transpose().template triangularView<Upper>()); // Not supported yet: trmm // VERIFY_IS_APPROX(sd*mcd*md.template triangularView<Lower>(), sd*mcd*md.template cast<CD>().eval().template triangularView<Lower>()); diff --git a/test/product_large.cpp b/test/product_large.cpp index 98f84c53b..845cd40ca 100644 --- a/test/product_large.cpp +++ b/test/product_large.cpp @@ -71,7 +71,7 @@ void test_product_large() std::ptrdiff_t m1 = internal::random<int>(10,100)*16; std::ptrdiff_t n1 = internal::random<int>(10,100)*16; // only makes sure it compiles fine - internal::computeProductBlockingSizes<float,float>(k1,m1,n1,1); + internal::computeProductBlockingSizes<float,float,std::ptrdiff_t>(k1,m1,n1,1); } { diff --git a/test/rand.cpp b/test/rand.cpp index 6790acf15..eeec34191 100644 --- a/test/rand.cpp +++ b/test/rand.cpp @@ -29,6 +29,9 @@ template<typename Scalar> void check_all_in_range(Scalar x, Scalar y) { mask( check_in_range(x,y)-x )++; } + for(Index i=0; i<mask.size(); ++i) + if(mask(i)==0) + std::cout << "WARNING: value " << x+i << " not reached." << std::endl; VERIFY( (mask>0).all() ); } diff --git a/test/svd_fill.h b/test/svd_fill.h index 7e44b3d05..1bbe645ee 100644 --- a/test/svd_fill.h +++ b/test/svd_fill.h @@ -80,6 +80,8 @@ void svd_fill_random(MatrixType &m, int Option = 0) Index i = internal::random<Index>(0,m.rows()-1); Index j = internal::random<Index>(0,m.cols()-1); m(j,i) = m(i,j) = samples(internal::random<Index>(0,samples.size()-1)); + if(NumTraits<Scalar>::IsComplex) + *(&numext::real_ref(m(j,i))+1) = *(&numext::real_ref(m(i,j))+1) = samples.real()(internal::random<Index>(0,samples.size()-1)); } } } @@ -91,8 +93,14 @@ void svd_fill_random(MatrixType &m, int Option = 0) if(!(dup && unit_uv)) { Index n = internal::random<Index>(0,m.size()-1); - for(Index i=0; i<n; ++i) - m(internal::random<Index>(0,m.rows()-1), internal::random<Index>(0,m.cols()-1)) = samples(internal::random<Index>(0,samples.size()-1)); + for(Index k=0; k<n; ++k) + { + Index i = internal::random<Index>(0,m.rows()-1); + Index j = internal::random<Index>(0,m.cols()-1); + m(i,j) = samples(internal::random<Index>(0,samples.size()-1)); + if(NumTraits<Scalar>::IsComplex) + *(&numext::real_ref(m(i,j))+1) = samples.real()(internal::random<Index>(0,samples.size()-1)); + } } } } diff --git a/test/swap.cpp b/test/swap.cpp index 5d6f0e6af..f76e3624d 100644 --- a/test/swap.cpp +++ b/test/swap.cpp @@ -74,10 +74,13 @@ template<typename MatrixType> void swap(const MatrixType& m) m1 = m1_copy; m3 = m3_copy; - // test assertion on mismatching size -- matrix case - VERIFY_RAISES_ASSERT(m1.swap(m1.row(0))); - // test assertion on mismatching size -- xpr case - VERIFY_RAISES_ASSERT(m1.row(0).swap(m1)); + if(m1.rows()>1) + { + // test assertion on mismatching size -- matrix case + VERIFY_RAISES_ASSERT(m1.swap(m1.row(0))); + // test assertion on mismatching size -- xpr case + VERIFY_RAISES_ASSERT(m1.row(0).swap(m1)); + } } void test_swap() diff --git a/test/vectorization_logic.cpp b/test/vectorization_logic.cpp index 35fbb9781..ee446c3c1 100644 --- a/test/vectorization_logic.cpp +++ b/test/vectorization_logic.cpp @@ -22,7 +22,11 @@ template<typename Dst, typename Src> bool test_assign(const Dst&, const Src&, int traversal, int unrolling) { typedef internal::copy_using_evaluator_traits<internal::evaluator<Dst>,internal::evaluator<Src>, internal::assign_op<typename Dst::Scalar> > traits; - bool res = traits::Traversal==traversal && traits::Unrolling==unrolling; + bool res = traits::Traversal==traversal; + if(unrolling==InnerUnrolling+CompleteUnrolling) + res = res && (int(traits::Unrolling)==InnerUnrolling || int(traits::Unrolling)==CompleteUnrolling); + else + res = res && int(traits::Unrolling)==unrolling; if(!res) { std::cerr << "Src: " << demangle_flags(Src::Flags) << std::endl; @@ -147,10 +151,10 @@ struct vectorization_logic VERIFY(test_assign(Matrix44c().col(1),Matrix44c().col(2)+Matrix44c().col(3), InnerVectorizedTraversal,CompleteUnrolling)); - + VERIFY(test_assign(Matrix44r().row(2),Matrix44r().row(1)+Matrix44r().row(1), InnerVectorizedTraversal,CompleteUnrolling)); - + if(PacketSize>1) { typedef Matrix<Scalar,3,3,ColMajor> Matrix33c; @@ -158,17 +162,29 @@ struct vectorization_logic LinearTraversal,CompleteUnrolling)); VERIFY(test_assign(Matrix33c().col(0),Matrix33c().col(1)+Matrix33c().col(1), LinearTraversal,CompleteUnrolling)); - - VERIFY(test_assign(Matrix3(),Matrix3().cwiseQuotient(Matrix3()), - PacketTraits::HasDiv ? LinearVectorizedTraversal : LinearTraversal,CompleteUnrolling)); - + + VERIFY(test_assign(Matrix3(),Matrix3().cwiseProduct(Matrix3()), + LinearVectorizedTraversal,CompleteUnrolling)); + VERIFY(test_assign(Matrix<Scalar,17,17>(),Matrix<Scalar,17,17>()+Matrix<Scalar,17,17>(), HalfPacketSize==1 ? InnerVectorizedTraversal : LinearTraversal,NoUnrolling)); - + VERIFY(test_assign(Matrix11(),Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(2,3)+Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(8,4), DefaultTraversal,PacketSize>4?InnerUnrolling:CompleteUnrolling)); + + VERIFY(test_assign(Vector1(),Matrix11()*Vector1(), + InnerVectorizedTraversal,CompleteUnrolling)); + + VERIFY(test_assign(Matrix11(),Matrix11().lazyProduct(Matrix11()), + InnerVectorizedTraversal,InnerUnrolling+CompleteUnrolling)); } - + + VERIFY(test_redux(Vector1(), + LinearVectorizedTraversal,CompleteUnrolling)); + + VERIFY(test_redux(Matrix<Scalar,PacketSize,3>(), + LinearVectorizedTraversal,CompleteUnrolling)); + VERIFY(test_redux(Matrix3(), LinearVectorizedTraversal,CompleteUnrolling)); @@ -226,6 +242,7 @@ struct vectorization_logic_half typedef Matrix<Scalar,PacketSize,1> Vector1; typedef Matrix<Scalar,PacketSize,PacketSize> Matrix11; typedef Matrix<Scalar,5*PacketSize,7,ColMajor> Matrix57; + typedef Matrix<Scalar,3*PacketSize,5,ColMajor> Matrix35; typedef Matrix<Scalar,5*PacketSize,7,DontAlign|ColMajor> Matrix57u; // typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16> Matrix44; // typedef Matrix<Scalar,(Matrix11::Flags&RowMajorBit)?16:4*PacketSize,(Matrix11::Flags&RowMajorBit)?4*PacketSize:16,DontAlign|EIGEN_DEFAULT_MATRIX_STORAGE_ORDER_OPTION> Matrix44u; @@ -291,12 +308,24 @@ struct vectorization_logic_half VERIFY(test_assign(Matrix11(),Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(2,3)+Matrix<Scalar,17,17>().template block<PacketSize,PacketSize>(8,4), DefaultTraversal,PacketSize>4?InnerUnrolling:CompleteUnrolling)); + + VERIFY(test_assign(Vector1(),Matrix11()*Vector1(), + InnerVectorizedTraversal,CompleteUnrolling)); + + VERIFY(test_assign(Matrix11(),Matrix11().lazyProduct(Matrix11()), + InnerVectorizedTraversal,InnerUnrolling+CompleteUnrolling)); } + VERIFY(test_redux(Vector1(), + LinearVectorizedTraversal,CompleteUnrolling)); + + VERIFY(test_redux(Matrix<Scalar,PacketSize,3>(), + LinearVectorizedTraversal,CompleteUnrolling)); + VERIFY(test_redux(Matrix3(), LinearVectorizedTraversal,CompleteUnrolling)); - VERIFY(test_redux(Matrix57(), + VERIFY(test_redux(Matrix35(), LinearVectorizedTraversal,CompleteUnrolling)); VERIFY(test_redux(Matrix57().template block<PacketSize,3>(1,0), |