// Solve LS problem M x = B, warning if M is nearly singular.
// Peter Vanroose, February 2000

#include <iostream>
#include <vnl/algo/vnl_svd.h>

template <class D> // D is often double or float
vnl_matrix<D>
solve_with_warning(const vnl_matrix<D> & M, const vnl_matrix<D> & B)
{
  // Take svd of vnl_matrix<D> M, setting singular values
  // smaller than 1e-8 to 0, and hold the result.
  const vnl_svd<D> svd(M, 1e-8);
  // Check for rank-deficiency
  if (svd.singularities() > 1)
    std::cerr << "Warning: Singular matrix, condition = " << svd.well_condition() << std::endl;
  return svd.solve(B);
}

template vnl_matrix<double>
solve_with_warning(const vnl_matrix<double> &, const vnl_matrix<double> &);

int
main()
{
  double data[] = { 1, 1, 1, 1, 2, 3, 1, 3, 6 };
  vnl_matrix<double> M(data, 3, 3);
  const vnl_matrix<double> B(3, 1, 7.0); // column vector [7 7 7]^T
  vnl_matrix<double> result = solve_with_warning(M, B);
  std::cerr << result << std::endl;
  M(2, 2) = 5;
  result = solve_with_warning(M, B);
  std::cerr << result << std::endl;
  return 0;
}
