12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152535455565758596061626364656667 |
- // 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()));
- }
|