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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2012 Desire Nuentsa Wakam <desire.nuentsa_wakam@inria.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
#define EIGEN_NO_DEBUG_SMALL_PRODUCT_BLOCKS
#include "sparse.h"
#include <Eigen/SPQRSupport>
template<typename MatrixType,typename DenseMat> int generate_sparse_rectangular_problem(MatrixType& A, DenseMat& dA, int maxRows = 300, int maxCols = 300) { eigen_assert(maxRows >= maxCols); typedef typename MatrixType::Scalar Scalar; int rows = internal::random<int>(1,maxRows); int cols = internal::random<int>(1,rows); double density = (std::max)(8./(rows*cols), 0.01); A.resize(rows,rows); dA.resize(rows,rows); initSparse<Scalar>(density, dA, A,ForceNonZeroDiag); A.makeCompressed(); return rows; }
template<typename Scalar> void test_spqr_scalar() { typedef SparseMatrix<Scalar,ColMajor> MatrixType; MatrixType A; Matrix<Scalar,Dynamic,Dynamic> dA; typedef Matrix<Scalar,Dynamic,1> DenseVector; DenseVector refX,x,b; SPQR<MatrixType> solver; generate_sparse_rectangular_problem(A,dA); Index m = A.rows(); b = DenseVector::Random(m); solver.compute(A); if (solver.info() != Success) { std::cerr << "sparse QR factorization failed\n"; exit(0); return; } x = solver.solve(b); if (solver.info() != Success) { std::cerr << "sparse QR factorization failed\n"; exit(0); return; } //Compare with a dense solver
refX = dA.colPivHouseholderQr().solve(b); VERIFY(x.isApprox(refX,test_precision<Scalar>())); } void test_spqr_support() { CALL_SUBTEST_1(test_spqr_scalar<double>()); CALL_SUBTEST_2(test_spqr_scalar<std::complex<double> >()); }
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