def predict_seasonal_components()

in python/prophet/forecaster.py [0:0]

• 23 lines of code
• 5 McCabe index (conditional complexity)

    def predict_seasonal_components(self, df):
        """Predict seasonality components, holidays, and added regressors.

        Parameters
        ----------
        df: Prediction dataframe.

        Returns
        -------
        Dataframe with seasonal components.
        """
        seasonal_features, _, component_cols, _ = (
            self.make_all_seasonality_features(df)
        )
        if self.uncertainty_samples:
            lower_p = 100 * (1.0 - self.interval_width) / 2
            upper_p = 100 * (1.0 + self.interval_width) / 2

        X = seasonal_features.values
        data = {}
        for component in component_cols.columns:
            beta_c = self.params['beta'] * component_cols[component].values

            comp = np.matmul(X, beta_c.transpose())
            if component in self.component_modes['additive']:
                comp *= self.y_scale
            data[component] = np.nanmean(comp, axis=1)
            if self.uncertainty_samples:
                data[component + '_lower'] = self.percentile(
                    comp, lower_p, axis=1,
                )
                data[component + '_upper'] = self.percentile(
                    comp, upper_p, axis=1,
                )
        return pd.DataFrame(data)