// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2009-2011 Jitse Niesen <jitse@maths.leeds.ac.uk> // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. #include "main.h" #include <unsupported/Eigen/MatrixFunctions> // For complex matrices, any matrix is fine. template<typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex> struct processTriangularMatrix { static void run(MatrixType&, MatrixType&, const MatrixType&) { } }; // For real matrices, make sure none of the eigenvalues are negative. template<typename MatrixType> struct processTriangularMatrix<MatrixType,0> { static void run(MatrixType& m, MatrixType& T, const MatrixType& U) { const Index size = m.cols(); for (Index i=0; i < size; ++i) { if (i == size - 1 || T.coeff(i+1,i) == 0) T.coeffRef(i,i) = std::abs(T.coeff(i,i)); else ++i; } m = U * T * U.transpose(); } }; template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex> struct generateTestMatrix; template <typename MatrixType> struct generateTestMatrix<MatrixType,0> { static void run(MatrixType& result, typename MatrixType::Index size) { result = MatrixType::Random(size, size); RealSchur<MatrixType> schur(result); MatrixType T = schur.matrixT(); processTriangularMatrix<MatrixType>::run(result, T, schur.matrixU()); } }; template <typename MatrixType> struct generateTestMatrix<MatrixType,1> { static void run(MatrixType& result, typename MatrixType::Index size) { result = MatrixType::Random(size, size); } }; template <typename Derived, typename OtherDerived> typename Derived::RealScalar relerr(const MatrixBase<Derived>& A, const MatrixBase<OtherDerived>& B) { return std::sqrt((A - B).cwiseAbs2().sum() / (std::min)(A.cwiseAbs2().sum(), B.cwiseAbs2().sum())); }