// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2008-2010 Gael Guennebaud // // 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 template bool test_random_setter(SparseMatrix& sm, const DenseType& ref, const std::vector& nonzeroCoords) { { sm.setZero(); SetterType w(sm); std::vector remaining = nonzeroCoords; while(!remaining.empty()) { int i = internal::random(0,static_cast(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 bool test_random_setter(DynamicSparseMatrix& sm, const DenseType& ref, const std::vector& nonzeroCoords) { sm.setZero(); std::vector remaining = nonzeroCoords; while(!remaining.empty()) { int i = internal::random(0,static_cast(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 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 DenseMatrix; typedef Matrix DenseVector; Scalar eps = 1e-6; SparseMatrixType m(rows, cols); DenseMatrix refMat = DenseMatrix::Zero(rows, cols); DenseVector vec1 = DenseVector::Random(rows); std::vector zeroCoords; std::vector nonzeroCoords; initSparse(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 >::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 w(m); // std::vector remaining = nonzeroCoords; // while(!remaining.empty()) // { // int i = internal::random(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 >(m,refMat,nonzeroCoords) )); #ifdef EIGEN_UNORDERED_MAP_SUPPORT VERIFY(( test_random_setter >(m,refMat,nonzeroCoords) )); #endif #ifdef _DENSE_HASH_MAP_H_ VERIFY(( test_random_setter >(m,refMat,nonzeroCoords) )); #endif #ifdef _SPARSE_HASH_MAP_H_ VERIFY(( test_random_setter >(m,refMat,nonzeroCoords) )); #endif // test RandomSetter /*{ SparseMatrixType m1(rows,cols), m2(rows,cols); DenseMatrix refM1 = DenseMatrix::Zero(rows, rows); initSparse(density, refM1, m1); { Eigen::RandomSetter setter(m2); for (int j=0; j void check_marketio() { typedef Matrix DenseMatrix; Index rows = internal::random(1,100); Index cols = internal::random(1,100); SparseMatrixType m1, m2; m1 = DenseMatrix::Random(rows, cols).sparseView(); saveMarket(m1, "sparse_extra.mtx"); loadMarket(m2, "sparse_extra.mtx"); VERIFY_IS_APPROX(m1,m2); } void test_sparse_extra() { for(int i = 0; i < g_repeat; i++) { int s = Eigen::internal::random(1,50); CALL_SUBTEST_1( sparse_extra(SparseMatrix(8, 8)) ); CALL_SUBTEST_2( sparse_extra(SparseMatrix >(s, s)) ); CALL_SUBTEST_1( sparse_extra(SparseMatrix(s, s)) ); CALL_SUBTEST_3( sparse_extra(DynamicSparseMatrix(s, s)) ); // CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix(s, s)) )); // CALL_SUBTEST_3(( sparse_basic(DynamicSparseMatrix(s, s)) )); CALL_SUBTEST_3( (sparse_product >()) ); CALL_SUBTEST_3( (sparse_product >()) ); CALL_SUBTEST_4( (check_marketio >()) ); CALL_SUBTEST_4( (check_marketio >()) ); CALL_SUBTEST_4( (check_marketio,ColMajor,int> >()) ); CALL_SUBTEST_4( (check_marketio,ColMajor,int> >()) ); CALL_SUBTEST_4( (check_marketio >()) ); CALL_SUBTEST_4( (check_marketio >()) ); CALL_SUBTEST_4( (check_marketio,ColMajor,long int> >()) ); CALL_SUBTEST_4( (check_marketio,ColMajor,long int> >()) ); TEST_SET_BUT_UNUSED_VARIABLE(s); } }