| // 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())); |
| } |