def makeNonFarmerHist(stdPerm, stdTran, numAgents, numPeriods):
NonFarmerParams = {
'BoroCnstArt': 0.0,
'CRRA': np.inf,
'CubicBool': True,
'DiscFac': 0.5,
'IncUnemp': 0.0,
'IncUnempRet': 0.0,
'LivPrb': [0.98],
'Nagents': 100,
'PermGroFac': [1.01],
'PermShkCount': 20,
'PermShkStd': [stdPerm],
'Rfree': 1.0,
'T_retire': 0,
'T_total': 1,
'TranShkCount': numAgents,
'TranShkStd': [stdTran],
'UnempPrb': 0.0,
'UnempPrbRet': 0.00,
'aXtraCount': 12,
'aXtraExtra': [None],
'aXtraMax': 20,
'aXtraMin': 0.001,
'aXtraNestFac': 3,
'tax_rate': 0.0,
'vFuncBool': False
}
PerfForNonFarmer = PerfForesightConsumerType(**NonFarmerParams)
PerfForNonFarmer.solve()
NonFarmer = IndShockConsumerType(**NonFarmerParams)
NonFarmer.solution = copy.deepcopy(PerfForNonFarmer.solution)
NonFarmer.addToTimeVary('solution')
NonFarmer.sim_periods = numPeriods
NonFarmer.initializeSim(sim_prds=NonFarmer.sim_periods)
NonFarmer.makeIncShkHist()
NonFarmer.simConsHistory()
NonFarmer.IncHist = np.multiply(NonFarmer.PermShkHist,
NonFarmer.TranShkHist)
NonFarmer.IncHist = np.reshape(
NonFarmer.IncHist, (NonFarmer.Nagents * NonFarmer.sim_periods, 1))
NonFarmer.cHist = np.reshape(
NonFarmer.cHist, (NonFarmer.Nagents * NonFarmer.sim_periods, 1))
NonFarmer.IncHist = list(itertools.chain.from_iterable(NonFarmer.IncHist))
NonFarmer.cHist = list(itertools.chain.from_iterable(NonFarmer.cHist))
return (NonFarmer.IncHist, NonFarmer.cHist)
from copy import deepcopy
from time import clock
from HARK.parallel import multiThreadCommands, multiThreadCommandsFake
# Set up a baseline IndShockConsumerType, which will be replicated.
# In this case, we use a completely arbitrary 10 period lifecycle.
TestType = IndShockConsumerType(**Params.init_lifecycle)
TestType.TestVar = np.empty(
TestType.AgentCount
) # This is for making an empty buffer for diagnostics
TestType.CubicBool = True # Cubic interpolation must be on, because that's what's used in OpenCL version
T_sim = 10 # Choose simulation length
AgentCount = 100 # Chose number of agents in each type
TestType.T_sim = T_sim # Choose number of periods to simulate
TestType.AgentCount = AgentCount
TestType.initializeSim() # Set up some objects for simulation
# Make a list with many copies of the baseline agent type, each with a different CRRA.
TypeCount = 100
CRRAmin = 1.0
CRRAmax = 5.0
CRRAset = np.linspace(CRRAmin, CRRAmax, TypeCount)
TypeList = []
for j in range(TypeCount):
NewType = deepcopy(TestType)
NewType(CRRA=CRRAset[j])
TypeList.append(NewType)
# Construct an instance of IndShockConsumerTypesOpenCL by passing the type list to the constructor.
# Note the plural in the class name; each instance of this class represents *several* types.
TestOpenCL = IndShockConsumerTypesOpenCL(TypeList)
