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147 lines
5.3 KiB
147 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 STORMEIGEN_NO_DEPRECATED_WARNING
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#include "sparse_basic.cpp"
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#include "sparse_product.cpp"
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#include <StormEigen/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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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 STORMEIGEN_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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StormEigen::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 = StormEigen::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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