code: def plot_predict(self, h=5, past_values=20, intervals=True,**kwargs):
          
          import matplotlib.pyplot as plt
          import seaborn as sns
  
          figsize = kwargs.get('figsize',(10,7))
  
          if self.latent_variables.estimated is False:
              raise Exception("No latent variables estimated!")
          else:
  
              predictions, variance, lower, upper = self._construct_predict(self.latent_variables.get_z_values(),h) 
              full_predictions = np.append(self.data,predictions)
              full_lower = np.append(self.data,lower)
              full_upper = np.append(self.data,upper)
              date_index = self.shift_dates(h)
  
              # Plot values (how far to look back)
              plot_values = full_predictions[-h-past_values:]*self._norm_std + self._norm_mean
              plot_index = date_index[-h-past_values:]
  
              # Lower and upper intervals
              lower = np.append(full_predictions[-h-1],lower)
              upper = np.append(full_predictions[-h-1],upper)
  
              plt.figure(figsize=figsize)
              if intervals == True:
                  plt.fill_between(date_index[-h-1:], 
                      lower*self._norm_std + self._norm_mean, 
                      upper*self._norm_std + self._norm_mean,
                      alpha=0.2)          
              
              plt.plot(plot_index,plot_values)
              plt.title("Forecast for " + self.data_name)
              plt.xlabel("Time")
              plt.ylabel(self.data_name)
              plt.show()
docs: Plots forecast with the estimated model
          
          Parameters
          ----------
          h : int (default : 5)
              How many steps ahead would you like to forecast?
          
          past_values : int (default : 20)
              How many past observations to show on the forecast graph?
          
          intervals : Boolean
              Would you like to show 95% prediction intervals for the forecast?
          
          Returns
          ----------
          - Plot of the forecast
          - Error bars, forecasted_values, plot_values, plot_index