101 lines
2.9 KiB
C++
101 lines
2.9 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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// Copyright (C) 2014 Gael Guennebaud <gael.guennebaud@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/SparseQR>
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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)
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{
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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,cols);
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dA.resize(rows,cols);
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initSparse<Scalar>(density, dA, A,ForceNonZeroDiag);
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A.makeCompressed();
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int nop = internal::random<int>(0, internal::random<double>(0,1) > 0.5 ? cols/2 : 0);
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for(int k=0; k<nop; ++k)
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{
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int j0 = internal::random<int>(0,cols-1);
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int j1 = internal::random<int>(0,cols-1);
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Scalar s = internal::random<Scalar>();
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A.col(j0) = s * A.col(j1);
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dA.col(j0) = s * dA.col(j1);
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}
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// if(rows<cols) {
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// A.conservativeResize(cols,cols);
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// dA.conservativeResize(cols,cols);
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// dA.bottomRows(cols-rows).setZero();
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// }
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return rows;
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}
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template<typename Scalar> void test_sparseqr_scalar()
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{
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typedef SparseMatrix<Scalar,ColMajor> MatrixType;
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typedef Matrix<Scalar,Dynamic,Dynamic> DenseMat;
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typedef Matrix<Scalar,Dynamic,1> DenseVector;
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MatrixType A;
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DenseMat dA;
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DenseVector refX,x,b;
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SparseQR<MatrixType, COLAMDOrdering<int> > solver;
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generate_sparse_rectangular_problem(A,dA);
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b = dA * DenseVector::Random(A.cols());
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solver.compute(A);
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if(internal::random<float>(0,1)>0.5)
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solver.factorize(A); // this checks that calling analyzePattern is not needed if the pattern do not change.
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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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VERIFY_IS_APPROX(A * x, b);
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//Compare with a dense QR solver
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ColPivHouseholderQR<DenseMat> dqr(dA);
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refX = dqr.solve(b);
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VERIFY_IS_EQUAL(dqr.rank(), solver.rank());
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if(solver.rank()==A.cols()) // full rank
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VERIFY_IS_APPROX(x, refX);
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// else
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// VERIFY((dA * refX - b).norm() * 2 > (A * x - b).norm() );
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// Compute explicitly the matrix Q
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MatrixType Q, QtQ, idM;
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Q = solver.matrixQ();
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//Check ||Q' * Q - I ||
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QtQ = Q * Q.adjoint();
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idM.resize(Q.rows(), Q.rows()); idM.setIdentity();
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VERIFY(idM.isApprox(QtQ));
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}
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void test_sparseqr()
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{
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for(int i=0; i<g_repeat; ++i)
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{
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CALL_SUBTEST_1(test_sparseqr_scalar<double>());
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CALL_SUBTEST_2(test_sparseqr_scalar<std::complex<double> >());
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}
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}
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