code: def updatepLvlNextFunc(self):
          '''
          A method that creates the pLvlNextFunc attribute as a sequence of
          linear functions, indicating constant expected permanent income growth
          across permanent income levels.  Draws on the attribute PermGroFac, and
          installs a special retirement function when it exists.
  
          Parameters
          ----------
          None
  
          Returns
          -------
          None
          '''
          orig_time = self.time_flow
          self.timeFwd()
  
          pLvlNextFunc = []
          for t in range(self.T_cycle):
              pLvlNextFunc.append(LinearInterp(np.array([0.,1.]),np.array([0.,self.PermGroFac[t]])))
  
          self.pLvlNextFunc = pLvlNextFunc
          self.addToTimeVary('pLvlNextFunc')
          if not orig_time:
              self.timeRev(f updatepLvlNextFunc(self):
          '''
          A method that creates the pLvlNextFunc attribute as a sequence of
          linear functions, indicating constant expected permanent income growth
          across permanent income levels.  Draws on the attribute PermGroFac, and
          installs a special retirement function when it exists.
  
          Parameters
          ----------
          None
  
          Returns
          -------
          None
          '''
          orig_time = self.time_flow
          self.timeFwd()
  
          pLvlNextFunc = []
          for t in range(self.T_cycle):
              pLvlNextFunc.append(LinearInterp(np.array([0.,1.]),np.array([0.,self.PermGroFac[t]])))
  
          self.pLvlNextFunc = pLvlNextFunc
          self.addToTimeVary('pLvlNextFunc')
          if not orig_time:
              self.timeRev()
docs: A method that creates the pLvlNextFunc attribute as a sequence of
          linear functions, indicating constant expected permanent income growth
          across permanent income levels.  Draws on the attribute PermGroFac, and
          installs a special retirement function when it exists.
  
          Parameters
          ----------
          None
  
          Returns
          -------
          None