code: def simBirth(self,which_agents):
          '''
          Makes new consumers for the given indices.  Slightly extends base method by also setting
          pLvlErrNow = 1.0 for new agents, indicating that they correctly perceive their productivity.
  
          Parameters
          ----------
          which_agents : np.array(Bool)
              Boolean array of size self.AgentCount indicating which agents should be "born".
  
          Returns
          -------
          None
          '''
          AggShockConsumerType.simBirth(self,which_agents)
          if hasattr(self,'pLvlErrNow'):
              self.pLvlErrNow[which_agents] = 1.0
          else:
              self.pLvlErrNow = np.ones(self.AgentCountf simBirth(self,which_agents):
          '''
          Makes new consumers for the given indices.  Slightly extends base method by also setting
          pLvlErrNow = 1.0 for new agents, indicating that they correctly perceive their productivity.
  
          Parameters
          ----------
          which_agents : np.array(Bool)
              Boolean array of size self.AgentCount indicating which agents should be "born".
  
          Returns
          -------
          None
          '''
          AggShockConsumerType.simBirth(self,which_agents)
          if hasattr(self,'pLvlErrNow'):
              self.pLvlErrNow[which_agents] = 1.0
          else:
              self.pLvlErrNow = np.ones(self.AgentCount)
docs: Makes new consumers for the given indices.  Slightly extends base method by also setting
          pLvlErrNow = 1.0 for new agents, indicating that they correctly perceive their productivity.
  
          Parameters
          ----------
          which_agents : np.array(Bool)
              Boolean array of size self.AgentCount indicating which agents should be "born".
  
          Returns
          -------
          None