TST: relax passthrough test tolerance when prices enter nonlinearly i…

…nto utility

tests/conftest.py

@@ -225,10 +225,10 @@ def medium_blp_simulation() -> SimulationFixture:
     characteristics, a demographic interacted with second-degree prices, an alternative ownership structure, and a
     scaled epsilon.
     """
-    id_data = build_id_data(T=4, J=25, F=6)
+    id_data = build_id_data(T=10, J=25, F=6)
     simulation = Simulation(
         product_formulations=(
-            Formulation('1 + x + y'),
+            Formulation('1 + x + prices'),
             Formulation('1 + I(prices**2)'),
             Formulation('1 + a + b')
         ),
@@ -238,20 +238,20 @@ def medium_blp_simulation() -> SimulationFixture:
             'clustering_ids': np.random.RandomState(1).choice(range(20), id_data.size),
             'ownership': build_ownership(id_data, lambda f, g: 1 if f == g else (0.1 if f > 3 and g > 3 else 0))
         },
-        beta=[1, 2, 1],
+        beta=[1, 2, -3],
         sigma=[
             [0.5, 0],
             [0.0, 0],
         ],
         pi=[
-            [+0],
-            [-3]
+            [+0.0],
+            [-0.1]
         ],
         gamma=[1, 1, 2],
         agent_formulation=Formulation('0 + f'),
         integration=Integration('product', 4),
-        xi_variance=0.0001,
-        omega_variance=0.0001,
+        xi_variance=0.00001,
+        omega_variance=0.00001,
         correlation=0.8,
         epsilon_scale=0.7,
         seed=1,

tests/test_blp.py

@@ -540,7 +540,7 @@ def test_costs(simulated_problem: SimulatedProblemFixture) -> None:
 @pytest.mark.usefixtures('simulated_problem')
 @pytest.mark.parametrize('iteration', [
     pytest.param(Iteration('simple', {'atol': 1e-12}), id="simple"),
-    pytest.param(Iteration('lm', {'xtol': 1e-12, 'ftol': 0}, compute_jacobian=True), id="LM"),
+    pytest.param(Iteration('hybr', {'xtol': 1e-12, 'ftol': 0}, compute_jacobian=True), id="Powell"),
 ])
 def test_prices(simulated_problem: SimulatedProblemFixture, iteration: Iteration) -> None:
     """Test that equilibrium prices computed with different methods are approximate the same.
@@ -781,13 +781,20 @@ def test_passthrough(simulated_problem: SimulatedProblemFixture) -> None:
     t = int(product_data.market_ids[0])
     costs = true_results.compute_costs(market_id=t)
 
+    # use a looser tolerance if prices enter nonlinearly into utility (this is harder to approximate)
+    atol = 1e-6
+    for key in ['X1', 'X2']:
+        for formulation in problem.products.dtype.fields[key][2]:
+            if any(s.name == 'prices' for s in formulation.differentiate('prices').free_symbols):
+                atol = 2e-3
+
     # compute the exact passthrough matrix and approximate it with finite differences
     exact = true_results.compute_passthrough(market_id=t)
     approximate = compute_finite_differences(
         lambda c: true_results.compute_prices(costs=c, market_id=t, iteration=Iteration('simple', {'atol': 1e-16})),
         costs,
     )
-    np.testing.assert_allclose(exact, approximate, atol=1e-6, rtol=0)
+    np.testing.assert_allclose(exact, approximate, atol=atol, rtol=0)
 
 
 @pytest.mark.usefixtures('simulated_problem')