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