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Drop EIGEN_USING_STD_MATH in favour of EIGEN_USING_STD

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This commit is contained in:
David Tellenbach
2020-10-09 02:05:05 +02:00
parent 183a208212
commit 4091f6b25c
14 changed files with 89 additions and 103 deletions
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24
Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
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@@ -410,7 +410,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType>
const InputType &matrix(a_matrix.derived());
EIGEN_USING_STD_MATH(abs);
EIGEN_USING_STD(abs);
eigen_assert(matrix.cols() == matrix.rows());
eigen_assert((options&~(EigVecMask|GenEigMask))==0
&& (options&EigVecMask)!=EigVecMask
@@ -489,7 +489,7 @@ template<typename MatrixType, typename DiagType, typename SubDiagType>
EIGEN_DEVICE_FUNC
ComputationInfo computeFromTridiagonal_impl(DiagType& diag, SubDiagType& subdiag, const Index maxIterations, bool computeEigenvectors, MatrixType& eivec)
{
EIGEN_USING_STD_MATH(abs);
EIGEN_USING_STD(abs);
ComputationInfo info;
typedef typename MatrixType::Scalar Scalar;
@@ -574,10 +574,10 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
EIGEN_DEVICE_FUNC
static inline void computeRoots(const MatrixType& m, VectorType& roots)
{
EIGEN_USING_STD_MATH(sqrt)
EIGEN_USING_STD_MATH(atan2)
EIGEN_USING_STD_MATH(cos)
EIGEN_USING_STD_MATH(sin)
EIGEN_USING_STD(sqrt)
EIGEN_USING_STD(atan2)
EIGEN_USING_STD(cos)
EIGEN_USING_STD(sin)
const Scalar s_inv3 = Scalar(1)/Scalar(3);
const Scalar s_sqrt3 = sqrt(Scalar(3));
@@ -613,8 +613,8 @@ template<typename SolverType> struct direct_selfadjoint_eigenvalues<SolverType,3
EIGEN_DEVICE_FUNC
static inline bool extract_kernel(MatrixType& mat, Ref<VectorType> res, Ref<VectorType> representative)
{
EIGEN_USING_STD_MATH(abs);
EIGEN_USING_STD_MATH(sqrt);
EIGEN_USING_STD(abs);
EIGEN_USING_STD(sqrt);
Index i0;
// Find non-zero column i0 (by construction, there must exist a non zero coefficient on the diagonal):
mat.diagonal().cwiseAbs().maxCoeff(&i0);
@@ -728,7 +728,7 @@ struct direct_selfadjoint_eigenvalues<SolverType,2,false>
EIGEN_DEVICE_FUNC
static inline void computeRoots(const MatrixType& m, VectorType& roots)
{
EIGEN_USING_STD_MATH(sqrt);
EIGEN_USING_STD(sqrt);
const Scalar t0 = Scalar(0.5) * sqrt( numext::abs2(m(0,0)-m(1,1)) + Scalar(4)*numext::abs2(m(1,0)));
const Scalar t1 = Scalar(0.5) * (m(0,0) + m(1,1));
roots(0) = t1 - t0;
@@ -738,8 +738,8 @@ struct direct_selfadjoint_eigenvalues<SolverType,2,false>
EIGEN_DEVICE_FUNC
static inline void run(SolverType& solver, const MatrixType& mat, int options)
{
EIGEN_USING_STD_MATH(sqrt);
EIGEN_USING_STD_MATH(abs);
EIGEN_USING_STD(sqrt);
EIGEN_USING_STD(abs);
eigen_assert(mat.cols() == 2 && mat.cols() == mat.rows());
eigen_assert((options&~(EigVecMask|GenEigMask))==0
@@ -816,7 +816,7 @@ template<int StorageOrder,typename RealScalar, typename Scalar, typename Index>
EIGEN_DEVICE_FUNC
static void tridiagonal_qr_step(RealScalar* diag, RealScalar* subdiag, Index start, Index end, Scalar* matrixQ, Index n)
{
EIGEN_USING_STD_MATH(abs);
EIGEN_USING_STD(abs);
RealScalar td = (diag[end-1] - diag[end])*RealScalar(0.5);
RealScalar e = subdiag[end-1];
// Note that thanks to scaling, e^2 or td^2 cannot overflow, however they can still