Merge pull request #895 from alan-turing-institute/model_params_fix

Overwrite defaults with user supplied param values

Author: radka-j

autoemulate/core/compare.py

@@ -406,14 +406,18 @@ def compare(self):
                                     "parameters",
                                     model_cls.__name__,
                                 )
-                                # extract default parameters from the model's __init__
+                                # Extract default parameters from the model's __init__
                                 init_sig = inspect.signature(model_cls.__init__)
-                                init_params = {
+                                default_params = {
                                     param_name: param.default
                                     for param_name, param in init_sig.parameters.items()
                                     if param_name in model_cls.get_tune_params()
                                 }
-                                best_params_for_this_model = init_params
+                                # Overwrite defaults with user-supplied values
+                                best_params_for_this_model = {
+                                    **default_params,
+                                    **self.model_params,
+                                }
 
                             self.logger.debug(
                                 'Running cross-validation for model "%s" '

tests/core/test_compare.py

@@ -102,6 +102,15 @@ def test_ae_no_tuning(sample_data_for_ae_compare):
     assert "likelihood_cls" in gp_params
 
 
+def test_ae_no_tuning_fix_params(sample_data_for_ae_compare):
+    """Test that model_params are correctly passed when tuning is disabled."""
+    x, y = sample_data_for_ae_compare
+    ae = AutoEmulate(
+        x, y, models=["GaussianProcessRBF"], model_params={"posterior_predictive": True}
+    )
+    assert ae.best_result().model.model.posterior_predictive is True  # pyright: ignore[reportAttributeAccessIssue]
+
+
 def test_get_model_subset():
     """Test getting a subset of models based on pytroch and probabilistic flags."""