1 // This file is part of Eigen, a lightweight C++ template library 2 // for linear algebra. 3 // 4 // Copyright (C) 2009-2011 Jitse Niesen <jitse@maths.leeds.ac.uk> 5 // 6 // This Source Code Form is subject to the terms of the Mozilla 7 // Public License v. 2.0. If a copy of the MPL was not distributed 8 // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. 9 10 #include "main.h" 11 #include <unsupported/Eigen/MatrixFunctions> 12 13 // For complex matrices, any matrix is fine. 14 template<typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex> 15 struct processTriangularMatrix 16 { runprocessTriangularMatrix17 static void run(MatrixType&, MatrixType&, const MatrixType&) 18 { } 19 }; 20 21 // For real matrices, make sure none of the eigenvalues are negative. 22 template<typename MatrixType> 23 struct processTriangularMatrix<MatrixType,0> 24 { 25 static void run(MatrixType& m, MatrixType& T, const MatrixType& U) 26 { 27 const Index size = m.cols(); 28 29 for (Index i=0; i < size; ++i) { 30 if (i == size - 1 || T.coeff(i+1,i) == 0) 31 T.coeffRef(i,i) = std::abs(T.coeff(i,i)); 32 else 33 ++i; 34 } 35 m = U * T * U.transpose(); 36 } 37 }; 38 39 template <typename MatrixType, int IsComplex = NumTraits<typename internal::traits<MatrixType>::Scalar>::IsComplex> 40 struct generateTestMatrix; 41 42 template <typename MatrixType> 43 struct generateTestMatrix<MatrixType,0> 44 { 45 static void run(MatrixType& result, typename MatrixType::Index size) 46 { 47 result = MatrixType::Random(size, size); 48 RealSchur<MatrixType> schur(result); 49 MatrixType T = schur.matrixT(); 50 processTriangularMatrix<MatrixType>::run(result, T, schur.matrixU()); 51 } 52 }; 53 54 template <typename MatrixType> 55 struct generateTestMatrix<MatrixType,1> 56 { 57 static void run(MatrixType& result, typename MatrixType::Index size) 58 { 59 result = MatrixType::Random(size, size); 60 } 61 }; 62 63 template <typename Derived, typename OtherDerived> 64 typename Derived::RealScalar relerr(const MatrixBase<Derived>& A, const MatrixBase<OtherDerived>& B) 65 { 66 return std::sqrt((A - B).cwiseAbs2().sum() / (std::min)(A.cwiseAbs2().sum(), B.cwiseAbs2().sum())); 67 } 68