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							67 lines
						
					
					
						
							2.0 KiB
						
					
					
				
			
		
		
		
			
			
			
				
					
				
				
					
				
			
		
		
	
	
							67 lines
						
					
					
						
							2.0 KiB
						
					
					
				
								// 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/StormEigen/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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								{
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								  static void run(MatrixType&, MatrixType&, const MatrixType&)
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								  { }
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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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								{
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								  static void run(MatrixType& m, MatrixType& T, const MatrixType& U)
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								  {
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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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								{
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								  static void run(MatrixType& result, typename MatrixType::Index size)
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								  {
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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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								{
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								  static void run(MatrixType& result, typename MatrixType::Index size)
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								  {
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								    result = MatrixType::Random(size, size);
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								  }
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								};
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								template <typename Derived, typename OtherDerived>
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								double relerr(const MatrixBase<Derived>& A, const MatrixBase<OtherDerived>& B)
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								{
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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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