class test_AgentType(unittest.TestCase):
def setUp(self):
self.agent = AgentType(cycles=1)
def test_solve(self):
self.agent.time_vary = ["vary_1"]
self.agent.time_inv = ["inv_1"]
self.agent.vary_1 = [1.1, 1.2, 1.3, 1.4]
self.agent.inv_1 = 1.05
# to test the superclass we create a dummy solve_one_period function
# for our agent, which doesn't do anything, instead of using a NullFunc
self.agent.solve_one_period = lambda vary_1: MetricObject()
self.agent.solve()
self.assertEqual(len(self.agent.solution), 4)
self.assertTrue(isinstance(self.agent.solution[0], MetricObject))
def test___repr__(self):
self.assertTrue('Parameters' in self.agent.__repr__())
def test___eq__(self):
agent2 = AgentType(cycles=1)
agent3 = AgentType(cycels=2)
self.assertEqual(self.agent, agent2)
self.assertNotEqual(self.agent, agent3)
class testAgentType(unittest.TestCase):
def setUp(self):
self.agent = AgentType()
def test_time(self):
self.agent.time_vary = ['var_1', 'var_2']
self.agent.var_1 = [4.3, 2, 1]
self.agent.var_2 = [1, 2, 3, 4, 5]
self.agent.timeFlip()
self.assertEqual(self.agent.var_1, [1, 2, 4.3])
self.assertEqual(self.agent.var_2, [5, 4, 3, 2, 1])
self.assertEqual(self.agent.time_flow, False)
self.agent.timeFlip()
self.assertEqual(self.agent.var_1, [4.3, 2, 1])
self.assertEqual(self.agent.var_2, [1, 2, 3, 4, 5])
self.assertEqual(self.agent.time_flow, True)
self.agent.timeRev()
self.assertEqual(self.agent.time_flow, False)
self.agent.timeFwd()
self.assertEqual(self.agent.time_flow, True)
def test_solve(self):
self.agent.time_vary = ['vary_1']
self.agent.time_inv = ['inv_1']
self.agent.vary_1 = [1.1, 1.2, 1.3, 1.4]
self.agent.inv_1 = 1.05
# to test the superclass we create a dummy solveOnePeriod function
# for our agent, which doesn't do anything, instead of using a NullFunc
self.agent.solveOnePeriod = lambda vary_1: HARKobject()
self.agent.solve()
self.assertEqual(len(self.agent.solution), 4)
self.assertTrue(isinstance(self.agent.solution[0], HARKobject))
class testAgentType(unittest.TestCase):
def setUp(self):
self.agent = AgentType()
def test_solve(self):
self.agent.time_vary = ['vary_1']
self.agent.time_inv = ['inv_1']
self.agent.vary_1 = [1.1, 1.2, 1.3, 1.4]
self.agent.inv_1 = 1.05
# to test the superclass we create a dummy solveOnePeriod function
# for our agent, which doesn't do anything, instead of using a NullFunc
self.agent.solveOnePeriod = lambda vary_1: HARKobject()
self.agent.solve()
self.assertEqual(len(self.agent.solution), 4)
self.assertTrue(isinstance(self.agent.solution[0], HARKobject))
def __init__(self, cycles=1, verbose=1, quiet=False, **kwds):
self.time_vary = []
self.time_inv = [
"CRRA", "Rfree", "DiscFac", "phi", "eta", "nu", "pssi", "B"
]
self.state_vars = []
self.shock_vars = []
self.solveOnePeriod = makeOnePeriodOOSolver(GLsolver)
self.__dict__.update(kwds)
cmin = 1e-6 # lower bound on consumption
Matlabgrid = loadmat('Bgrid')
griddata = list(Matlabgrid.items())
datagrid_array = np.array(griddata)
Bgrid_uc = datagrid_array[3, 1]
params = init_GL.copy()
params.update(kwds)
kwds = params
#setup grid based on constraint phi
#Rfree= 1.00625
#phi=1.60054
self.Bgrid = []
for i in range(200):
if Bgrid_uc[0, i] > -self.phi:
self.Bgrid.append(Bgrid_uc[0, i])
self.Bgrid = np.array(self.Bgrid).reshape(1, len(self.Bgrid))
#initial Guess for Cpolicy
Cguess = np.maximum(
(self.Rfree - 1) * np.ones(13).reshape(13, 1).dot(self.Bgrid),
cmin)
self.solution_terminal_ = GLConsumerSolution(Cpol=Cguess, )
AgentType.__init__(self,
solution_terminal=deepcopy(self.solution_terminal_),
cycles=cycles,
pseudo_terminal=False,
**kwds)
self.verbose = verbose
self.quiet = quiet
self.solveOnePeriod = makeOnePeriodOOSolver(GLsolver)
def setUp(self):
self.agent = AgentType(cycles=1)
def setUp(self):
self.agent = AgentType(cycles=1, AgentCount=3)
def test___eq__(self):
agent2 = AgentType(cycles=1)
agent3 = AgentType(cycels=2)
self.assertEqual(self.agent, agent2)
self.assertNotEqual(self.agent, agent3)
def setUp(self):
self.agent = AgentType()