code: def projection_error(nodes, projected):
      
      relative_err = np.linalg.norm(nodes - projected, ord="fro")
      if relative_err != 0.0:
          relative_err /= np.linalg.norm(nodes, ord="fro")
      return relative_err
docs: Compute the error between ``nodes`` and the projected nodes.
  
      .. note::
  
          This is a helper for :func:`maybe_reduce`, which is in turn a helper
          for :func:`_full_reduce`. Hence there is no corresponding Fortran
          speedup.
  
      For now, just compute the relative error in the Frobenius norm. But,
      we may wish to consider the error per row / point instead.
  
      Args:
          nodes (numpy.ndarray): Nodes in a curve.
          projected (numpy.ndarray): The ``nodes`` projected into the
              space of degree-elevated nodes.
  
      Returns:
          float: The relative error.