// This file is part of Eigen, a lightweight C++ template library // for linear algebra. // // Copyright (C) 2011 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/. #include "sparse.h" #include template void check_sparse_solving(Solver& solver, const typename Solver::MatrixType& A, const Rhs& b, const DenseMat& dA, const DenseRhs& db) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; DenseRhs refX = dA.lu().solve(db); { Rhs x(b.rows(), b.cols()); Rhs oldb = b; solver.compute(A); if (solver.info() != Success) { std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n"; exit(0); return; } x = solver.solve(b); if (solver.info() != Success) { std::cerr << "sparse solver testing: solving failed\n"; return; } VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!"); VERIFY(x.isApprox(refX,test_precision())); x.setZero(); // test the analyze/factorize API solver.analyzePattern(A); solver.factorize(A); if (solver.info() != Success) { std::cerr << "sparse solver testing: factorization failed (check_sparse_solving)\n"; exit(0); return; } x = solver.solve(b); if (solver.info() != Success) { std::cerr << "sparse solver testing: solving failed\n"; return; } VERIFY(oldb.isApprox(b) && "sparse solver testing: the rhs should not be modified!"); VERIFY(x.isApprox(refX,test_precision())); } // test dense Block as the result and rhs: { DenseRhs x(db.rows(), db.cols()); DenseRhs oldb(db); x.setZero(); x.block(0,0,x.rows(),x.cols()) = solver.solve(db.block(0,0,db.rows(),db.cols())); VERIFY(oldb.isApprox(db) && "sparse solver testing: the rhs should not be modified!"); VERIFY(x.isApprox(refX,test_precision())); } } template void check_sparse_solving_real_cases(Solver& solver, const typename Solver::MatrixType& A, const Rhs& b, const Rhs& refX) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; typedef typename Mat::RealScalar RealScalar; Rhs x(b.rows(), b.cols()); solver.compute(A); if (solver.info() != Success) { std::cerr << "sparse solver testing: factorization failed (check_sparse_solving_real_cases)\n"; exit(0); return; } x = solver.solve(b); if (solver.info() != Success) { std::cerr << "sparse solver testing: solving failed\n"; return; } RealScalar res_error; // Compute the norm of the relative error if(refX.size() != 0) res_error = (refX - x).norm()/refX.norm(); else { // Compute the relative residual norm res_error = (b - A * x).norm()/b.norm(); } if (res_error > test_precision() ){ std::cerr << "Test " << g_test_stack.back() << " failed in "EI_PP_MAKE_STRING(__FILE__) << " (" << EI_PP_MAKE_STRING(__LINE__) << ")" << std::endl << std::endl; abort(); } } template void check_sparse_determinant(Solver& solver, const typename Solver::MatrixType& A, const DenseMat& dA) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; solver.compute(A); if (solver.info() != Success) { std::cerr << "sparse solver testing: factorization failed (check_sparse_determinant)\n"; return; } Scalar refDet = dA.determinant(); VERIFY_IS_APPROX(refDet,solver.determinant()); } template void check_sparse_abs_determinant(Solver& solver, const typename Solver::MatrixType& A, const DenseMat& dA) { using std::abs; typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; solver.compute(A); if (solver.info() != Success) { std::cerr << "sparse solver testing: factorization failed (check_sparse_abs_determinant)\n"; return; } Scalar refDet = abs(dA.determinant()); VERIFY_IS_APPROX(refDet,solver.absDeterminant()); } template int generate_sparse_spd_problem(Solver& , typename Solver::MatrixType& A, typename Solver::MatrixType& halfA, DenseMat& dA, int maxSize = 300) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; typedef Matrix DenseMatrix; int size = internal::random(1,maxSize); double density = (std::max)(8./(size*size), 0.01); Mat M(size, size); DenseMatrix dM(size, size); initSparse(density, dM, M, ForceNonZeroDiag); A = M * M.adjoint(); dA = dM * dM.adjoint(); halfA.resize(size,size); if(Solver::UpLo==(Lower|Upper)) halfA = A; else halfA.template selfadjointView().rankUpdate(M); return size; } #ifdef TEST_REAL_CASES template inline std::string get_matrixfolder() { std::string mat_folder = TEST_REAL_CASES; if( internal::is_same >::value || internal::is_same >::value ) mat_folder = mat_folder + static_cast("/complex/"); else mat_folder = mat_folder + static_cast("/real/"); return mat_folder; } #endif template void check_sparse_spd_solving(Solver& solver) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; typedef SparseMatrix SpMat; typedef Matrix DenseMatrix; typedef Matrix DenseVector; // generate the problem Mat A, halfA; DenseMatrix dA; for (int i = 0; i < g_repeat; i++) { int size = generate_sparse_spd_problem(solver, A, halfA, dA); // generate the right hand sides int rhsCols = internal::random(1,16); double density = (std::max)(8./(size*rhsCols), 0.1); SpMat B(size,rhsCols); DenseVector b = DenseVector::Random(size); DenseMatrix dB(size,rhsCols); initSparse(density, dB, B, ForceNonZeroDiag); check_sparse_solving(solver, A, b, dA, b); check_sparse_solving(solver, halfA, b, dA, b); check_sparse_solving(solver, A, dB, dA, dB); check_sparse_solving(solver, halfA, dB, dA, dB); check_sparse_solving(solver, A, B, dA, dB); check_sparse_solving(solver, halfA, B, dA, dB); // check only once if(i==0) { b = DenseVector::Zero(size); check_sparse_solving(solver, A, b, dA, b); } } // First, get the folder #ifdef TEST_REAL_CASES if (internal::is_same::value || internal::is_same >::value) return ; std::string mat_folder = get_matrixfolder(); MatrixMarketIterator it(mat_folder); for (; it; ++it) { if (it.sym() == SPD){ Mat halfA; PermutationMatrix pnull; halfA.template selfadjointView() = it.matrix().template triangularView().twistedBy(pnull); std::cout<< " ==== SOLVING WITH MATRIX " << it.matname() << " ==== \n"; check_sparse_solving_real_cases(solver, it.matrix(), it.rhs(), it.refX()); check_sparse_solving_real_cases(solver, halfA, it.rhs(), it.refX()); } } #endif } template void check_sparse_spd_determinant(Solver& solver) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; typedef Matrix DenseMatrix; // generate the problem Mat A, halfA; DenseMatrix dA; generate_sparse_spd_problem(solver, A, halfA, dA, 30); for (int i = 0; i < g_repeat; i++) { check_sparse_determinant(solver, A, dA); check_sparse_determinant(solver, halfA, dA ); } } template int generate_sparse_square_problem(Solver&, typename Solver::MatrixType& A, DenseMat& dA, int maxSize = 300) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; int size = internal::random(1,maxSize); double density = (std::max)(8./(size*size), 0.01); A.resize(size,size); dA.resize(size,size); initSparse(density, dA, A, ForceNonZeroDiag); return size; } template void check_sparse_square_solving(Solver& solver) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; typedef SparseMatrix SpMat; typedef Matrix DenseMatrix; typedef Matrix DenseVector; int rhsCols = internal::random(1,16); Mat A; DenseMatrix dA; for (int i = 0; i < g_repeat; i++) { int size = generate_sparse_square_problem(solver, A, dA); A.makeCompressed(); DenseVector b = DenseVector::Random(size); DenseMatrix dB(size,rhsCols); SpMat B(size,rhsCols); double density = (std::max)(8./(size*rhsCols), 0.1); initSparse(density, dB, B, ForceNonZeroDiag); B.makeCompressed(); check_sparse_solving(solver, A, b, dA, b); check_sparse_solving(solver, A, dB, dA, dB); check_sparse_solving(solver, A, B, dA, dB); // check only once if(i==0) { b = DenseVector::Zero(size); check_sparse_solving(solver, A, b, dA, b); } } // First, get the folder #ifdef TEST_REAL_CASES if (internal::is_same::value || internal::is_same >::value) return ; std::string mat_folder = get_matrixfolder(); MatrixMarketIterator it(mat_folder); for (; it; ++it) { std::cout<< " ==== SOLVING WITH MATRIX " << it.matname() << " ==== \n"; check_sparse_solving_real_cases(solver, it.matrix(), it.rhs(), it.refX()); } #endif } template void check_sparse_square_determinant(Solver& solver) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; typedef Matrix DenseMatrix; // generate the problem Mat A; DenseMatrix dA; generate_sparse_square_problem(solver, A, dA, 30); A.makeCompressed(); for (int i = 0; i < g_repeat; i++) { check_sparse_determinant(solver, A, dA); } } template void check_sparse_square_abs_determinant(Solver& solver) { typedef typename Solver::MatrixType Mat; typedef typename Mat::Scalar Scalar; typedef Matrix DenseMatrix; // generate the problem Mat A; DenseMatrix dA; generate_sparse_square_problem(solver, A, dA, 30); A.makeCompressed(); for (int i = 0; i < g_repeat; i++) { check_sparse_abs_determinant(solver, A, dA); } }