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()