'Covariance parameters for each mixture component.
The shape depends on ``cvtype``::
(n_states, n_features)                if \'spherical\',
(n_features, n_features)              if \'tied\',
(n_states, n_features)                if \'diag\',
(n_states, n_features, n_features)    if \'full\''

def _get_covars(self):

    if (self.covariance_type == 'full'):
        return self.covars_
    elif (self.covariance_type == 'diag'):
        return [np.diag(cov) for cov in self.covars_]
    elif (self.covariance_type == 'tied'):
        return ([self.covars_] * self.n_components)
    elif (self.covariance_type == 'spherical'):
        return [np.diag(cov) for cov in self.covars_]
