updates to tests based on @Mv77's review. econ-ark#1105

sbenthall · Sep 27, 2022 · e822f2f · e822f2f
1 parent 3371efd
commit e822f2f
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Showing 5 changed files with 19 additions and 15 deletions.
diff --git a/HARK/ConsumptionSaving/tests/test_ConsAggShockModel.py b/HARK/ConsumptionSaving/tests/test_ConsAggShockModel.py
@@ -189,15 +189,16 @@ def test_methods(self):
 
         # testing update_solution_terminal()
         self.assertEqual(
-            self.agent.solution_terminal.cFunc[0](10, 13.32722),
+            self.agent.solution_terminal.cFunc[0](10, self.economy.MSS),
             10
         )
 
         self.assertAlmostEqual(
             self.economy.agents[0].solution[0].cFunc[0](
-                10, 13.32722
+                10, self.economy.MSS
             ).tolist(),
-            1.2386774
+            1.2386774,
+            places = 4
         )
 
         self.assertAlmostEqual(

diff --git a/HARK/ConsumptionSaving/tests/test_ConsPortfolioModel.py b/HARK/ConsumptionSaving/tests/test_ConsPortfolioModel.py
@@ -79,7 +79,7 @@ def test_sim_one_period(self):
         )
 
         # a drawn shock ; may not be robust to RNG/disitrubition implementations
-        self.assertAlmostEqual(self.pcct.shocks["Adjust"][0], 1.0)
+        #self.assertAlmostEqual(self.pcct.shocks["Adjust"][0], 1.0)
 
 
 class SimulatePortfolioConsumerTypeTestCase(PortfolioConsumerTypeTestCase):

diff --git a/HARK/ConsumptionSaving/tests/test_IndShockConsumerType.py b/HARK/ConsumptionSaving/tests/test_IndShockConsumerType.py
@@ -94,7 +94,8 @@ def test_simulated_values(self):
         self.agent.initialize_sim()
         self.agent.simulate()
 
-        self.assertAlmostEqual(self.agent.MPCnow[1], 0.5711503906043797)
+        # MPCnow depends on assets, which are stochastic
+        #self.assertAlmostEqual(self.agent.MPCnow[1], 0.5711503906043797)
 
         # simulation test -- seed/generator specific
         #self.assertAlmostEqual(self.agent.state_now["aLvl"][1], 0.18438326264597635)
@@ -704,9 +705,9 @@ def test_Harmenberg_mtd(self):
         # simulation tests -- seed/generator specific
         # But these are based on aggregate population statistics.
         # WARNING: May fail stochastically, or based on specific RNG types.
-        self.assertAlmostEqual(c_std2, 0.0376882)
-        self.assertAlmostEqual(c_std1, 0.0044117)
-        self.assertAlmostEqual(c_std_ratio, 8.5426941)
+        #self.assertAlmostEqual(c_std2, 0.0376882, places = 2)
+        #self.assertAlmostEqual(c_std1, 0.0044117, places = 2)
+        #self.assertAlmostEqual(c_std_ratio, 8.5426941, places = 2)
 
 
 # %% Shock pre-computing tests

diff --git a/HARK/ConsumptionSaving/tests/test_IndShockConsumerTypeFast.py b/HARK/ConsumptionSaving/tests/test_IndShockConsumerTypeFast.py
@@ -57,7 +57,9 @@ def test_ConsIndShockSolverBasic(self):
     def test_simulated_values(self):
         self.agent.initialize_sim()
         self.agent.simulate()
-        self.assertAlmostEqual(self.agent.MPCnow[1], 0.5711503906043797)
+
+        #MPCnow is stochastic
+        #self.assertAlmostEqual(self.agent.MPCnow[1], 0.5711503906043797)
 
         # simulation test -- seed/generator specific
         # self.assertAlmostEqual(self.agent.state_now['aLvl'][1], 0.18438326264597635)

diff --git a/HARK/tests/test_distribution.py b/HARK/tests/test_distribution.py
@@ -312,16 +312,16 @@ def test_MVNormal(self):
         ## Are these tests generator/backend specific?
         dist = MVNormal()
 
-        self.assertTrue(
-            np.allclose(dist.draw(1)[0], np.array([2.76405235, 1.40015721]))
-        )
+        #self.assertTrue(
+        #    np.allclose(dist.draw(1)[0], np.array([2.76405235, 1.40015721]))
+        #)
 
         dist.draw(100)
         dist.reset()
 
-        self.assertTrue(
-            np.allclose(dist.draw(1)[0], np.array([2.76405235, 1.40015721]))
-        )
+        #self.assertTrue(
+        #    np.allclose(dist.draw(1)[0], np.array([2.76405235, 1.40015721]))
+        #)
 
     def test_Weibull(self):
         Weibull().draw(1)[0]