forecaster.py 文件源码

def predict(self, df=None):
        """Predict using the prophet model.

        Parameters
        ----------
        df: pd.DataFrame with dates for predictions (column ds), and capacity
            (column cap) if logistic growth. If not provided, predictions are
            made on the history.

        Returns
        -------
        A pd.DataFrame with the forecast components.
        """
        if df is None:
            df = self.history.copy()
        else:
            if df.shape[0] == 0:
                raise ValueError('Dataframe has no rows.')
            df = self.setup_dataframe(df.copy())

        df['trend'] = self.predict_trend(df)
        seasonal_components = self.predict_seasonal_components(df)
        intervals = self.predict_uncertainty(df)

        # Drop columns except ds, cap, floor, and trend
        cols = ['ds', 'trend']
        if 'cap' in df:
            cols.append('cap')
        if self.logistic_floor:
            cols.append('floor')
        # Add in forecast components
        df2 = pd.concat((df[cols], intervals, seasonal_components), axis=1)
        df2['yhat'] = df2['trend'] + df2['seasonal']
        return df2