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