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
#self.pSocial[which_agents] = (self.pSocial[which_agents]*float(2*self.NetSiz+1)-self.Pcvd[which_agents]+self.PlvlAggNow)/(2*self.NetSiz+1)
self.PSocial[which_agents] = self.PlvlAggNow
self.Pcvd[which_agents] = self.PlvlAggNow
self.Pcvd_pre[which_agents] = self.PlvlAggNow
self.pInd[which_agents] = 1.0
self.pLvlNow[which_agents] = self.PlvlAggNow
else:
self.pLvlErrNow = np.ones(self.AgentCount)
self.PSocial = np.ones(self.AgentCount)
self.Pcvd = np.ones(self.AgentCount)
self.Pcvd_pre = np.ones(self.AgentCount)
self.pInd = np.ones(self.AgentCount)
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.AgentCount)
