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							63 lines
						
					
					
						
							2.3 KiB
						
					
					
				
			
		
		
		
			
			
			
				
					
				
				
					
				
			
		
		
	
	
							63 lines
						
					
					
						
							2.3 KiB
						
					
					
				
								// This file is part of Eigen, a lightweight C++ template library
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								// for linear algebra. Eigen itself is part of the KDE project.
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								//
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								// Copyright (C) 2008 Gael Guennebaud <g.gael@free.fr>
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								// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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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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								// this hack is needed to make this file compiles with -pedantic (gcc)
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								#ifdef __GNUC__
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								#define throw(X)
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								#endif
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								// discard stack allocation as that too bypasses malloc
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								#define EIGEN_STACK_ALLOCATION_LIMIT 0
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								// any heap allocation will raise an assert
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								#define EIGEN_NO_MALLOC
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								#include "main.h"
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								template<typename MatrixType> void nomalloc(const MatrixType& m)
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								{
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								  /* this test check no dynamic memory allocation are issued with fixed-size matrices
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								  */
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								  typedef typename MatrixType::Scalar Scalar;
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								  typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType;
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								  int rows = m.rows();
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								  int cols = m.cols();
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								  MatrixType m1 = MatrixType::Random(rows, cols),
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								             m2 = MatrixType::Random(rows, cols),
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								             m3(rows, cols),
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								             mzero = MatrixType::Zero(rows, cols),
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								             identity = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
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								                              ::Identity(rows, rows),
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								             square = Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime>
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								                              ::Random(rows, rows);
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								  VectorType v1 = VectorType::Random(rows),
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								             v2 = VectorType::Random(rows),
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								             vzero = VectorType::Zero(rows);
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								  Scalar s1 = ei_random<Scalar>();
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								  int r = ei_random<int>(0, rows-1),
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								      c = ei_random<int>(0, cols-1);
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								  VERIFY_IS_APPROX((m1+m2)*s1,              s1*m1+s1*m2);
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								  VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c)));
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								  VERIFY_IS_APPROX(m1.cwise() * m1.block(0,0,rows,cols), m1.cwise() * m1);
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								  VERIFY_IS_APPROX((m1*m1.transpose())*m2,  m1*(m1.transpose()*m2));
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								}
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								void test_eigen2_nomalloc()
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								{
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								  // check that our operator new is indeed called:
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								  VERIFY_RAISES_ASSERT(MatrixXd dummy = MatrixXd::Random(3,3));
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								  CALL_SUBTEST_1( nomalloc(Matrix<float, 1, 1>()) );
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								  CALL_SUBTEST_2( nomalloc(Matrix4d()) );
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								  CALL_SUBTEST_3( nomalloc(Matrix<float,32,32>()) );
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								}
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