C++ (Cpp) generate_sparse_rectangular_problem Examples

Example #1

File: spqr_support.cpp Project: 1165048017/convnet-1

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);
  
  int 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>()));
}

Example #2

File: sparseqr.cpp Project: muhammedabdelnasser/Vehicle-Steering-Using-Model-Predictive-Control

template<typename Scalar> void test_sparseqr_scalar()
{
  typedef SparseMatrix<Scalar,ColMajor> MatrixType; 
  typedef Matrix<Scalar,Dynamic,Dynamic> DenseMat;
  typedef Matrix<Scalar,Dynamic,1> DenseVector;
  MatrixType A;
  DenseMat dA;
  DenseVector refX,x,b; 
  SparseQR<MatrixType, COLAMDOrdering<int> > solver; 
  generate_sparse_rectangular_problem(A,dA);
  
  b = dA * DenseVector::Random(A.cols());
  solver.compute(A);
  if(internal::random<float>(0,1)>0.5f)
    solver.factorize(A);  // this checks that calling analyzePattern is not needed if the pattern do not change.
  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;
  }
  
  VERIFY_IS_APPROX(A * x, b);
  
  //Compare with a dense QR solver
  ColPivHouseholderQR<DenseMat> dqr(dA);
  refX = dqr.solve(b);
  
  VERIFY_IS_EQUAL(dqr.rank(), solver.rank());
  if(solver.rank()==A.cols()) // full rank
    VERIFY_IS_APPROX(x, refX);
//   else
//     VERIFY((dA * refX - b).norm() * 2 > (A * x - b).norm() );

  // Compute explicitly the matrix Q
  MatrixType Q, QtQ, idM;
  Q = solver.matrixQ();
  //Check  ||Q' * Q - I ||
  QtQ = Q * Q.adjoint();
  idM.resize(Q.rows(), Q.rows()); idM.setIdentity();
  VERIFY(idM.isApprox(QtQ));
  
  // Q to dense
  DenseMat dQ;
  dQ = solver.matrixQ();
  VERIFY_IS_APPROX(Q, dQ);
}