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							148 lines
						
					
					
						
							5.3 KiB
						
					
					
				
			
		
		
		
			
			
			
				
					
				
				
					
				
			
		
		
	
	
							148 lines
						
					
					
						
							5.3 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) 2008-2010 Gael Guennebaud <g.gael@free.fr>
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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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								// import basic and product tests for deprectaed DynamicSparseMatrix
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								#define EIGEN_NO_DEPRECATED_WARNING
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								#include "sparse_basic.cpp"
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								#include "sparse_product.cpp"
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								#include <Eigen/SparseExtra>
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								template<typename SetterType,typename DenseType, typename Scalar, int Options>
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								bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
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								{
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								  {
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								    sm.setZero();
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								    SetterType w(sm);
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								    std::vector<Vector2i> remaining = nonzeroCoords;
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								    while(!remaining.empty())
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								    {
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								      int i = internal::random<int>(0,static_cast<int>(remaining.size())-1);
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								      w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
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								      remaining[i] = remaining.back();
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								      remaining.pop_back();
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								    }
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								  }
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								  return sm.isApprox(ref);
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								}
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								template<typename SetterType,typename DenseType, typename T>
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								bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
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								{
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								  sm.setZero();
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								  std::vector<Vector2i> remaining = nonzeroCoords;
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								  while(!remaining.empty())
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								  {
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								    int i = internal::random<int>(0,static_cast<int>(remaining.size())-1);
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								    sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
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								    remaining[i] = remaining.back();
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								    remaining.pop_back();
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								  }
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								  return sm.isApprox(ref);
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								}
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								template<typename SparseMatrixType> void sparse_extra(const SparseMatrixType& ref)
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								{
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								  typedef typename SparseMatrixType::Index Index;
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								  const Index rows = ref.rows();
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								  const Index cols = ref.cols();
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								  typedef typename SparseMatrixType::Scalar Scalar;
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								  enum { Flags = SparseMatrixType::Flags };
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								  double density = (std::max)(8./(rows*cols), 0.01);
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								  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
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								  typedef Matrix<Scalar,Dynamic,1> DenseVector;
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								  Scalar eps = 1e-6;
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								  SparseMatrixType m(rows, cols);
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								  DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
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								  DenseVector vec1 = DenseVector::Random(rows);
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								  std::vector<Vector2i> zeroCoords;
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								  std::vector<Vector2i> nonzeroCoords;
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								  initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
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								  if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
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								    return;
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								  // test coeff and coeffRef
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								  for (int i=0; i<(int)zeroCoords.size(); ++i)
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								  {
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								    VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
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								    if(internal::is_same<SparseMatrixType,SparseMatrix<Scalar,Flags> >::value)
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								      VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
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								  }
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								  VERIFY_IS_APPROX(m, refMat);
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								  m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
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								  refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
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								  VERIFY_IS_APPROX(m, refMat);
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								  // random setter
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								//   {
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								//     m.setZero();
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								//     VERIFY_IS_NOT_APPROX(m, refMat);
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								//     SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
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								//     std::vector<Vector2i> remaining = nonzeroCoords;
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								//     while(!remaining.empty())
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								//     {
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								//       int i = internal::random<int>(0,remaining.size()-1);
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								//       w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
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								//       remaining[i] = remaining.back();
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								//       remaining.pop_back();
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								//     }
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								//   }
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								//   VERIFY_IS_APPROX(m, refMat);
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								    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
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								    #ifdef EIGEN_UNORDERED_MAP_SUPPORT
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								    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
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								    #endif
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								    #ifdef _DENSE_HASH_MAP_H_
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								    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
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								    #endif
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								    #ifdef _SPARSE_HASH_MAP_H_
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								    VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
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								    #endif
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								  // test RandomSetter
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								  /*{
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								    SparseMatrixType m1(rows,cols), m2(rows,cols);
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								    DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
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								    initSparse<Scalar>(density, refM1, m1);
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								    {
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								      Eigen::RandomSetter<SparseMatrixType > setter(m2);
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								      for (int j=0; j<m1.outerSize(); ++j)
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								        for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
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								          setter(i.index(), j) = i.value();
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								    }
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								    VERIFY_IS_APPROX(m1, m2);
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								  }*/
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								}
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								void test_sparse_extra()
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								{
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								  for(int i = 0; i < g_repeat; i++) {
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								    int s = Eigen::internal::random<int>(1,50);
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								    CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(8, 8)) );
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								    CALL_SUBTEST_2( sparse_extra(SparseMatrix<std::complex<double> >(s, s)) );
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								    CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(s, s)) );
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								    CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix<double>(s, s)) );
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								//    CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double>(s, s)) ));
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								//    CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double,ColMajor,long int>(s, s)) ));
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								    CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, ColMajor> >()) );
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								    CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, RowMajor> >()) );
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								  }
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								}
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