forecaster.py 文件源码

def make_all_seasonality_features(self, df):
        """Dataframe with seasonality features.

        Includes seasonality features, holiday features, and added regressors.

        Parameters
        ----------
        df: pd.DataFrame with dates for computing seasonality features and any
            added regressors.

        Returns
        -------
        pd.DataFrame with regression features.
        list of prior scales for each column of the features dataframe.
        """
        seasonal_features = []
        prior_scales = []

        # Seasonality features
        for name, props in self.seasonalities.items():
            features = self.make_seasonality_features(
                df['ds'],
                props['period'],
                props['fourier_order'],
                name,
            )
            seasonal_features.append(features)
            prior_scales.extend(
                [props['prior_scale']] * features.shape[1])

        # Holiday features
        if self.holidays is not None:
            features, holiday_priors = self.make_holiday_features(df['ds'])
            seasonal_features.append(features)
            prior_scales.extend(holiday_priors)

        # Additional regressors
        for name, props in self.extra_regressors.items():
            seasonal_features.append(pd.DataFrame(df[name]))
            prior_scales.append(props['prior_scale'])

        if len(seasonal_features) == 0:
            seasonal_features.append(
                pd.DataFrame({'zeros': np.zeros(df.shape[0])}))
            prior_scales.append(1.)
        return pd.concat(seasonal_features, axis=1), prior_scales