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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 _initialize_sufficient_statistics(self):
 """Initializes sufficient statistics required for M-step. The method is *pure*, meaning that it doesn't change the state of the instance. For extensibility computed statistics are stored in a dictionary. Returns ------- nobs : int Number of samples in the data. start : array, shape (n_components, ) An array where the i-th element corresponds to the posterior probability of the first sample being generated by the i-th state. trans : array, shape (n_components, n_components) An array where the (i, j)-th element corresponds to the posterior probability of transitioning between the i-th to j-th states. """

        stats = {'nobs': 0,
                 'start': np.zeros(self.n_components),
                 'trans': np.zeros((self.n_components, self.n_components))}
        return stats