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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008-2010 Gael Guennebaud <g.gael@free.fr>
//
// 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/.
// import basic and product tests for deprecated DynamicSparseMatrix
#if 0 // sparse_basic(DynamicSparseMatrix) does not compile at all -> disabled
static long g_realloc_count = 0;
#define EIGEN_SPARSE_COMPRESSED_STORAGE_REALLOCATE_PLUGIN g_realloc_count++;
static long g_dense_op_sparse_count = 0;
#define EIGEN_SPARSE_ASSIGNMENT_FROM_DENSE_OP_SPARSE_PLUGIN g_dense_op_sparse_count++;
#define EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_ADD_DENSE_PLUGIN g_dense_op_sparse_count+=10;
#define EIGEN_SPARSE_ASSIGNMENT_FROM_SPARSE_SUB_DENSE_PLUGIN g_dense_op_sparse_count+=20;
#define EIGEN_SPARSE_TEST_INCLUDED_FROM_SPARSE_EXTRA 1
#endif
#define EIGEN_NO_DEPRECATED_WARNING
// Disable counting of temporaries, since sparse_product(DynamicSparseMatrix)
// has an extra copy-assignment.
#define EIGEN_SPARSE_PRODUCT_IGNORE_TEMPORARY_COUNT
#include "sparse_product.cpp"
#if 0 // sparse_basic(DynamicSparseMatrix) does not compile at all -> disabled
#include "sparse_basic.cpp"
#endif
#include <Eigen/SparseExtra>
template<typename SetterType,typename DenseType, typename Scalar, int Options>
bool test_random_setter(SparseMatrix<Scalar,Options>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
{
{
sm.setZero();
SetterType w(sm);
std::vector<Vector2i> remaining = nonzeroCoords;
while(!remaining.empty())
{
int i = internal::random<int>(0,static_cast<int>(remaining.size())-1);
w(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
remaining[i] = remaining.back();
remaining.pop_back();
}
}
return sm.isApprox(ref);
}
template<typename SetterType,typename DenseType, typename T>
bool test_random_setter(DynamicSparseMatrix<T>& sm, const DenseType& ref, const std::vector<Vector2i>& nonzeroCoords)
{
sm.setZero();
std::vector<Vector2i> remaining = nonzeroCoords;
while(!remaining.empty())
{
int i = internal::random<int>(0,static_cast<int>(remaining.size())-1);
sm.coeffRef(remaining[i].x(),remaining[i].y()) = ref.coeff(remaining[i].x(),remaining[i].y());
remaining[i] = remaining.back();
remaining.pop_back();
}
return sm.isApprox(ref);
}
template<typename SparseMatrixType> void sparse_extra(const SparseMatrixType& ref)
{
const Index rows = ref.rows();
const Index cols = ref.cols();
typedef typename SparseMatrixType::Scalar Scalar;
enum { Flags = SparseMatrixType::Flags };
double density = (std::max)(8./(rows*cols), 0.01);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
Scalar eps = 1e-6;
SparseMatrixType m(rows, cols);
DenseMatrix refMat = DenseMatrix::Zero(rows, cols);
DenseVector vec1 = DenseVector::Random(rows);
std::vector<Vector2i> zeroCoords;
std::vector<Vector2i> nonzeroCoords;
initSparse<Scalar>(density, refMat, m, 0, &zeroCoords, &nonzeroCoords);
if (zeroCoords.size()==0 || nonzeroCoords.size()==0)
return;
// test coeff and coeffRef
for (int i=0; i<(int)zeroCoords.size(); ++i)
{
VERIFY_IS_MUCH_SMALLER_THAN( m.coeff(zeroCoords[i].x(),zeroCoords[i].y()), eps );
if(internal::is_same<SparseMatrixType,SparseMatrix<Scalar,Flags> >::value)
VERIFY_RAISES_ASSERT( m.coeffRef(zeroCoords[0].x(),zeroCoords[0].y()) = 5 );
}
VERIFY_IS_APPROX(m, refMat);
m.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
refMat.coeffRef(nonzeroCoords[0].x(), nonzeroCoords[0].y()) = Scalar(5);
VERIFY_IS_APPROX(m, refMat);
// random setter
// {
// m.setZero();
// VERIFY_IS_NOT_APPROX(m, refMat);
// SparseSetter<SparseMatrixType, RandomAccessPattern> w(m);
// std::vector<Vector2i> remaining = nonzeroCoords;
// while(!remaining.empty())
// {
// int i = internal::random<int>(0,remaining.size()-1);
// w->coeffRef(remaining[i].x(),remaining[i].y()) = refMat.coeff(remaining[i].x(),remaining[i].y());
// remaining[i] = remaining.back();
// remaining.pop_back();
// }
// }
// VERIFY_IS_APPROX(m, refMat);
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdMapTraits> >(m,refMat,nonzeroCoords) ));
#ifdef EIGEN_UNORDERED_MAP_SUPPORT
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, StdUnorderedMapTraits> >(m,refMat,nonzeroCoords) ));
#endif
#ifdef EIGEN_GOOGLEHASH_SUPPORT
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) ));
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleSparseHashMapTraits> >(m,refMat,nonzeroCoords) ));
#endif
// test RandomSetter
/*{
SparseMatrixType m1(rows,cols), m2(rows,cols);
DenseMatrix refM1 = DenseMatrix::Zero(rows, rows);
initSparse<Scalar>(density, refM1, m1);
{
Eigen::RandomSetter<SparseMatrixType > setter(m2);
for (int j=0; j<m1.outerSize(); ++j)
for (typename SparseMatrixType::InnerIterator i(m1,j); i; ++i)
setter(i.index(), j) = i.value();
}
VERIFY_IS_APPROX(m1, m2);
}*/
}
template<typename SparseMatrixType>
void check_marketio()
{
typedef Matrix<typename SparseMatrixType::Scalar, Dynamic, Dynamic> DenseMatrix;
Index rows = internal::random<Index>(1,100);
Index cols = internal::random<Index>(1,100);
SparseMatrixType m1, m2;
m1 = DenseMatrix::Random(rows, cols).sparseView();
saveMarket(m1, "sparse_extra.mtx");
loadMarket(m2, "sparse_extra.mtx");
VERIFY_IS_EQUAL(DenseMatrix(m1),DenseMatrix(m2));
}
template<typename VectorType>
void check_marketio_vector()
{
Index size = internal::random<Index>(1,100);
VectorType v1, v2;
v1 = VectorType::Random(size);
saveMarketVector(v1, "vector_extra.mtx");
loadMarketVector(v2, "vector_extra.mtx");
VERIFY_IS_EQUAL(v1,v2);
}
EIGEN_DECLARE_TEST(sparse_extra)
{
for(int i = 0; i < g_repeat; i++) {
int s = Eigen::internal::random<int>(1,50);
CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(8, 8)) );
CALL_SUBTEST_2( sparse_extra(SparseMatrix<std::complex<double> >(s, s)) );
CALL_SUBTEST_1( sparse_extra(SparseMatrix<double>(s, s)) );
CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix<double>(s, s)) );
// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double>(s, s)) ));
// CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix<double,ColMajor,long int>(s, s)) ));
CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, ColMajor> >()) );
CALL_SUBTEST_3( (sparse_product<DynamicSparseMatrix<float, RowMajor> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<float,ColMajor,int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<double,ColMajor,int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<std::complex<float>,ColMajor,int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<std::complex<double>,ColMajor,int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<float,ColMajor,long int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<double,ColMajor,long int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<std::complex<float>,ColMajor,long int> >()) );
CALL_SUBTEST_4( (check_marketio<SparseMatrix<std::complex<double>,ColMajor,long int> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<float,1,Dynamic> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<double,1,Dynamic> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<std::complex<float>,1,Dynamic> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<std::complex<double>,1,Dynamic> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<float,Dynamic,1> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<double,Dynamic,1> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<std::complex<float>,Dynamic,1> >()) );
CALL_SUBTEST_5( (check_marketio_vector<Matrix<std::complex<double>,Dynamic,1> >()) );
TEST_SET_BUT_UNUSED_VARIABLE(s);
}
}
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