How to use the fbprophet.models.prophet_stan_model function in fbprophet

'X': seasonal_features,
            'sigmas': prior_scales,
            'tau': self.changepoint_prior_scale,
            'trend_indicator': int(self.growth == 'logistic'),
            's_a': component_cols['additive_terms'],
            's_m': component_cols['multiplicative_terms'],
        }

        if self.growth == 'linear':
            dat['cap'] = np.zeros(self.history.shape[0])
            kinit = self.linear_growth_init(history)
        else:
            dat['cap'] = history['cap_scaled']
            kinit = self.logistic_growth_init(history)

        model = prophet_stan_model

        def stan_init():
            return {
                'k': kinit[0],
                'm': kinit[1],
                'delta': np.zeros(len(self.changepoints_t)),
                'beta': np.zeros(seasonal_features.shape[1]),
                'sigma_obs': 1,
            }

        if (
                (history['y'].min() == history['y'].max())
                and self.growth == 'linear'
        ):
            # Nothing to fit.
            self.params = stan_init()