Remove get_models.py module

OpenSourceEconomics · Feb 28, 2024 · a3005c4 · a3005c4
1 parent 456bb79
commit a3005c4
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Showing 8 changed files with 48 additions and 158 deletions.
diff --git a/src/lcm/get_model.py b/src/lcm/get_model.py
diff --git a/tests/data/regression_tests/simulation.pkl b/tests/data/regression_tests/simulation.pkl
diff --git a/tests/data/regression_tests/solution.pkl b/tests/data/regression_tests/solution.pkl
diff --git a/tests/test_analytical_solution.py b/tests/test_analytical_solution.py
@@ -4,42 +4,67 @@
 import pytest
 from lcm._config import TEST_DATA
 from lcm.entry_point import get_lcm_function
-from lcm.get_model import get_model
 from numpy.testing import assert_array_almost_equal as aaae
 
+from tests.test_models.phelps_deaton import PHELPS_DEATON_WITH_FILTERS
+
+# ======================================================================================
+# Model specifications
+# ======================================================================================
+
+ISKHAVOV_2017_PARAMS = {
+    "beta": 0.98,
+    "utility": {"disutility_of_work": None},
+    "next_wealth": {
+        "interest_rate": 0.0,
+        "wage": 20.0,
+    },
+}
+
 TEST_CASES = {
-    "iskhakov_2017_five_periods": get_model("iskhakov_2017_five_periods"),
-    "iskhakov_2017_low_delta": get_model(
-        "iskhakov_2017_low_disutility_of_work",
-    ),
+    "iskhakov_2017_five_periods": {
+        "model": {**PHELPS_DEATON_WITH_FILTERS, "n_periods": 5},
+        "params": {**ISKHAVOV_2017_PARAMS, "utility": {"disutility_of_work": 1.0}},
+    },
+    "iskhakov_2017_low_delta": {
+        "model": {**PHELPS_DEATON_WITH_FILTERS, "n_periods": 3},
+        "params": {**ISKHAVOV_2017_PARAMS, "utility": {"disutility_of_work": 0.1}},
+    },
 }
 
 
 def mean_square_error(x, y, axis=None):
     return np.mean((x - y) ** 2, axis=axis)
 
 
-@pytest.mark.parametrize(("model_name", "model_config"), TEST_CASES.items())
-def test_analytical_solution(model_name, model_config):
+# ======================================================================================
+# Test
+# ======================================================================================
+
+
+@pytest.mark.parametrize(("model_name", "model_and_params"), TEST_CASES.items())
+def test_analytical_solution(model_name, model_and_params):
     """Test that the numerical solution matches the analytical solution.
 
     The analytical solution is from Iskhakov et al (2017) and is generated
     in the development repository: github.com/opensourceeconomics/lcm-dev.
 
     """
+    # ----------------------------------------------------------------------------------
     # Compute LCM solution
-    # ==================================================================================
-    solve_model, _ = get_lcm_function(model=model_config.model)
+    # ----------------------------------------------------------------------------------
+    solve_model, _ = get_lcm_function(model=model_and_params["model"])
 
-    vf_arr_list = solve_model(params=model_config.params)
+    vf_arr_list = solve_model(params=model_and_params["params"])
     _numerical = np.stack(vf_arr_list)
     numerical = {
         "worker": _numerical[:, 0, :],
         "retired": _numerical[:, 1, :],
     }
 
+    # ----------------------------------------------------------------------------------
     # Load analytical solution
-    # ==================================================================================
+    # ----------------------------------------------------------------------------------
     analytical = {
         _type: np.genfromtxt(
             TEST_DATA.joinpath(
@@ -51,8 +76,9 @@ def test_analytical_solution(model_name, model_config):
         for _type in ["worker", "retired"]
     }
 
+    # ----------------------------------------------------------------------------------
     # Compare
-    # ==================================================================================
+    # ----------------------------------------------------------------------------------
     for _type in ["worker", "retired"]:
         _analytical = np.array(analytical[_type])
         _numerical = numerical[_type]

diff --git a/tests/test_models/phelps_deaton.py b/tests/test_models/phelps_deaton.py
@@ -103,15 +103,15 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
         "consumption": {
             "grid_type": "linspace",
             "start": 1,
-            "stop": 100,
+            "stop": 400,
             "n_points": N_GRID_POINTS["consumption"],
         },
     },
     "states": {
         "wealth": {
             "grid_type": "linspace",
             "start": 1,
-            "stop": 100,
+            "stop": 400,
             "n_points": N_GRID_POINTS["wealth"],
         },
     },
@@ -134,7 +134,7 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
         "wealth": {
             "grid_type": "linspace",
             "start": 1,
-            "stop": 100,
+            "stop": 400,
             "n_points": N_GRID_POINTS["wealth"],
         },
     },
@@ -156,15 +156,15 @@ def absorbing_retirement_filter(retirement, lagged_retirement):
         "consumption": {
             "grid_type": "linspace",
             "start": 1,
-            "stop": 100,
+            "stop": 400,
             "n_points": N_GRID_POINTS["consumption"],
         },
     },
     "states": {
         "wealth": {
             "grid_type": "linspace",
             "start": 1,
-            "stop": 100,
+            "stop": 400,
             "n_points": N_GRID_POINTS["wealth"],
         },
         "lagged_retirement": {"options": [0, 1]},

diff --git a/tests/test_process_model.py b/tests/test_process_model.py
@@ -122,14 +122,14 @@ def test_process_phelps_deaton_with_filters():
     # Gridspecs
     wealth_specs = GridSpec(
         kind="linspace",
-        specs={"start": 0, "stop": 100, "n_points": N_GRID_POINTS["wealth"]},
+        specs={"start": 1, "stop": 400, "n_points": N_GRID_POINTS["wealth"]},
     )
 
     assert model.gridspecs["wealth"] == wealth_specs
 
     consumption_specs = GridSpec(
         kind="linspace",
-        specs={"start": 1, "stop": 100, "n_points": N_GRID_POINTS["consumption"]},
+        specs={"start": 1, "stop": 400, "n_points": N_GRID_POINTS["consumption"]},
     )
     assert model.gridspecs["consumption"] == consumption_specs
 
@@ -173,14 +173,14 @@ def test_process_phelps_deaton():
     # Gridspecs
     wealth_specs = GridSpec(
         kind="linspace",
-        specs={"start": 0, "stop": 100, "n_points": N_GRID_POINTS["wealth"]},
+        specs={"start": 1, "stop": 400, "n_points": N_GRID_POINTS["wealth"]},
     )
 
     assert model.gridspecs["wealth"] == wealth_specs
 
     consumption_specs = GridSpec(
         kind="linspace",
-        specs={"start": 0, "stop": 100, "n_points": N_GRID_POINTS["consumption"]},
+        specs={"start": 1, "stop": 400, "n_points": N_GRID_POINTS["consumption"]},
     )
     assert model.gridspecs["consumption"] == consumption_specs
 

diff --git a/tests/test_simulate.py b/tests/test_simulate.py
@@ -140,7 +140,7 @@ def test_simulate_using_get_lcm_function(phelps_deaton_model_solution, n_periods
         params,
         vf_arr_list=vf_arr_list,
         initial_states={
-            "wealth": jnp.array([1.0, 20, 40, 70]),
+            "wealth": jnp.array([20.0, 150, 250, 320]),
         },
         additional_targets=["utility", "consumption_constraint"],
     )

diff --git a/.../test_analytical_solution_on_toy_model.py → tests/test_solution_on_toy_model.py b/.../test_analytical_solution_on_toy_model.py → tests/test_solution_on_toy_model.py