diff --git a/tests/glm/test_golden_master.py b/tests/glm/test_golden_master.py index dc6d5646..716edfff 100644 --- a/tests/glm/test_golden_master.py +++ b/tests/glm/test_golden_master.py @@ -215,13 +215,13 @@ def test_gm_storage(distribution, data_all_storage, expected_all): model = fit_model( data=data, family=distribution, - model_parameters={}, + model_parameters={"alpha": 1.0}, use_weights=False, use_offset=False, cv=False, ) - run_name = "default" + run_name = "regularization" expected = expected_all[distribution][run_name] assert_gm_allclose(model, expected) @@ -234,7 +234,7 @@ def test_gm_custom_link(family_link, use_weights, use_offset, data_all, expected """Currently only testing log-linear model.""" distribution, link = family_link data = data_all[distribution] - model_parameters = {"link": link} + model_parameters = {"link": link, "alpha": 1.0} model = fit_model( data=data, family=distribution, @@ -265,9 +265,7 @@ def test_gm_approx_hessian( distribution, use_weights, use_offset, data_all, expected_all ): data = data_all[distribution] - model_parameters = { - "hessian_approx": 0.1, - } + model_parameters = {"hessian_approx": 0.1, "alpha": 1.0} model = fit_model( data=data, family=distribution, @@ -277,7 +275,7 @@ def test_gm_approx_hessian( cv=False, ) - run_name = "default" + run_name = "regularization" if use_weights: run_name = f"{run_name}_weights" if use_offset: @@ -298,6 +296,7 @@ def test_gm_cv(distribution, data_all, expected_all): "alphas": [0.1, 0.05, 0.01], "l1_ratio": [0.2, 0.5, 0.9], "cv": 3, + "alpha": 1.0, } model = fit_model( data=data, @@ -453,7 +452,7 @@ def run_and_store_golden_master( for use_offset in [True, False]: gm_dict = run_and_store_golden_master( distribution=dist, - model_parameters={"link": link}, + model_parameters={"link": link, "alpha": 1.0}, run_name=f"custom-{dist}-{link}", use_weights=use_weights, use_offset=use_offset,