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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 deprectaed DynamicSparseMatrix
#define EIGEN_NO_DEPRECATED_WARNING
#include "sparse_basic.cpp"
#include "sparse_product.cpp"
#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 _DENSE_HASH_MAP_H_
VERIFY(( test_random_setter<RandomSetter<SparseMatrixType, GoogleDenseHashMapTraits> >(m,refMat,nonzeroCoords) )); #endif
#ifdef _SPARSE_HASH_MAP_H_
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); { StormEigen::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); }*/
}
void test_sparse_extra() { for(int i = 0; i < g_repeat; i++) { int s = StormEigen::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> >()) ); } }
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