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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def projection_error(nodes, projected):
 """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. """

    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