forecaster.py 文件源码

def predictive_samples(self, df):
        """Sample from the posterior predictive distribution.

        Parameters
        ----------
        df: Dataframe with dates for predictions (column ds), and capacity
            (column cap) if logistic growth.

        Returns
        -------
        Dictionary with keys "trend", "seasonal", and "yhat" containing
        posterior predictive samples for that component. "seasonal" is the sum
        of seasonalities, holidays, and added regressors.
        """
        df = self.setup_dataframe(df.copy())
        sim_values = self.sample_posterior_predictive(df)
        return sim_values