def plot_forecast(self, steps=1, figsize=(10, 10)):
        """
        Plot h-step ahead forecasts against actual realizations of time
        series. Note that forecasts are lined up with their respective
        realizations.

        Parameters
        ----------
        steps :
        """
        import matplotlib.pyplot as plt

        fig, axes = plt.subplots(figsize=figsize, nrows=self.neqs,
                                 sharex=True)

        forc = self.forecast(steps=steps)
        dates = forc.index

        y_overlay = self.y.reindex(dates)

        for i, col in enumerate(forc.columns):
            ax = axes[i]

            y_ts = y_overlay[col]
            forc_ts = forc[col]

            y_handle = ax.plot(dates, y_ts.values, 'k.', ms=2)
            forc_handle = ax.plot(dates, forc_ts.values, 'k-')

        fig.legend((y_handle, forc_handle), ('Y', 'Forecast'))
        fig.autofmt_xdate()

        fig.suptitle(steps % 'Dynamic %d-step forecast')

        # pretty things up a bit
        plotting.adjust_subplots(bottom=0.15, left=0.10)
        plt.draw_if_interactive()
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/vector_ar/dynamic.py/DynamicVAR.plot_forecast/swapped operands of `%`