code: def update(self):
          '''
          Use primitive parameters (and perfect foresight calibrations) to make
          interest factor and wage rate functions (of capital to labor ratio),
          as well as discrete approximations to the aggregate shock distributions.
  
          Parameters
          ----------
          None
  
          Returns
          -------
          None
          '''
          CobbDouglasEconomy.update(self)
          StateCount = self.MrkvArray.shape[0]
          AFunc_all = []
          for i in range(StateCount):
              AFunc_all.append(AggregateSavingRule(self.intercept_prev[i],self.slope_prev[i]))
          self.AFunc = AFunc_alf update(self):
          '''
          Use primitive parameters (and perfect foresight calibrations) to make
          interest factor and wage rate functions (of capital to labor ratio),
          as well as discrete approximations to the aggregate shock distributions.
  
          Parameters
          ----------
          None
  
          Returns
          -------
          None
          '''
          CobbDouglasEconomy.update(self)
          StateCount = self.MrkvArray.shape[0]
          AFunc_all = []
          for i in range(StateCount):
              AFunc_all.append(AggregateSavingRule(self.intercept_prev[i],self.slope_prev[i]))
          self.AFunc = AFunc_all
docs: Use primitive parameters (and perfect foresight calibrations) to make
          interest factor and wage rate functions (of capital to labor ratio),
          as well as discrete approximations to the aggregate shock distributions.
  
          Parameters
          ----------
          None
  
          Returns
          -------
          None