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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 _as_reference_point(self) -> np.ndarray: """ Return classification information as reference point """

        ref_val = []
        for fn, f in self._classification.items():
            if f[0] == "<":
                ref_val.append(self._method.problem.ideal[fn])
            elif f[0] == "<>":
                ref_val.append(self._method.problem.nadir[fn])
            else:
                ref_val.append(f[1])

        return np.array(ref_val)