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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 delaunay_reduce(lattice, eps=1e-5):
 """Run Delaunay reduction Args: lattice: Lattice parameters in the form of [[a_x, a_y, a_z], [b_x, b_y, b_z], [c_x, c_y, c_z]] symprec: float: Tolerance to check if volume is close to zero or not and if two basis vectors are orthogonal by the value of dot product being close to zero or not. Returns: if the Delaunay reduction succeeded: Reduced lattice parameters are given as a numpy 'double' array: [[a_x, a_y, a_z], [b_x, b_y, b_z], [c_x, c_y, c_z]] otherwise None is returned. """

    _set_no_error()

    delaunay_lattice = np.array(np.transpose(lattice),
                                dtype='double', order='C')
    result = spg.delaunay_reduce(delaunay_lattice, float(eps))
    _set_error_message()

    if result == 0:
        return None
    else:
        return np.array(np.transpose(delaunay_lattice),
                        dtype='double', order='C')