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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 _compute_stddevs(self, C, mag, rjb, imt, stddev_types):
 """ Compute total standard deviation, equations 5 and 6, page 48. """

        # aleatory uncertainty
        sigma_ale_m = np.interp(mag, [5.0, 5.5, 8.0],
                                [C['m50'], C['m55'], C['m80']])
        sigma_ale_rjb = np.interp(rjb, [5.0, 20.0], [C['r5'], C['r20']])
        sigma_ale = np.sqrt(sigma_ale_m ** 2 + sigma_ale_rjb ** 2)

        # epistemic uncertainty
        if imt.period < 1:
            sigma_epi = 0.36 + 0.07 * (mag - 6)
        else:
            sigma_epi = 0.34 + 0.06 * (mag - 6)

        sigma_total = np.sqrt(sigma_ale ** 2 + sigma_epi ** 2)

        stddevs = []
        for _ in stddev_types:
            stddevs.append(sigma_total)

        return stddevs