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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 _vec_b(self, donor_catchments):
 """ Return vector ``b`` of model error covariances to estimate weights Methodology source: Kjeldsen, Jones and Morris, 2009, eqs 3 and 10 :param donor_catchments: Catchments to use as donors :type donor_catchments: list of :class:`Catchment` :return: Model error covariance vector :rtype: :class:`numpy.ndarray` """

        p = len(donor_catchments)
        b = 0.1175 * np.ones(p)
        for i in range(p):
            b[i] *= self._model_error_corr(self.catchment, donor_catchments[i])
        return b