Merge pull request xopt-org#222 from ChristopherMayes/fixed_features_…

…improvements add robustness and additional test to fixed features functionality in Bayesian generators
YektaY · Apr 23, 2024 · 0b64028 · 0b64028
2 parents a613b00 + c32a23f
commit 0b64028
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Showing 4 changed files with 126 additions and 20 deletions.
diff --git a/docs/examples/single_objective_bayes_opt/fixed_features.ipynb b/docs/examples/single_objective_bayes_opt/fixed_features.ipynb
diff --git a/tests/generators/bayesian/test_bayesian_generator.py b/tests/generators/bayesian/test_bayesian_generator.py
@@ -239,3 +239,12 @@ def test_fixed_feature(self):
             model.models[0].input_transform.bounds,
             torch.tensor(((0, 0), (1, 10))).double(),
         )
+
+        # test bad fixed feature name
+        gen = BayesianGenerator(vocs=TEST_VOCS_BASE)
+        gen.fixed_features = {"bad_name": 3.0}
+        data = deepcopy(TEST_VOCS_DATA)
+        gen.add_data(data)
+
+        with pytest.raises(KeyError):
+            gen.train_model()
diff --git a/tests/test_vocs.py b/tests/test_vocs.py
@@ -27,6 +27,14 @@ def test_empty_objectives(self):
             variables={"x": [0, 1]},
         )
 
+    def test_output_names(self):
+        test_vocs = VOCS(
+            variables={"x": [0, 1]},
+            objectives={"y1": "MINIMIZE"},
+            constraints={"c1": ["GREATER_THAN", 0], "c2": ["LESS_THAN", 0]},
+        )
+        assert test_vocs.output_names == ["y1", "c1", "c2"]
+
     def test_constraint_specification(self):
         good_constraint_list = [
             ["LESS_THAN", 0],

diff --git a/xopt/generators/bayesian/bayesian_generator.py b/xopt/generators/bayesian/bayesian_generator.py
@@ -375,6 +375,11 @@ def train_model(self, data: pd.DataFrame = None, update_internal=True) -> Module
             # get bounds for each fixed_feature (vocs bounds take precedent)
             for key in self.fixed_features:
                 if key not in variable_bounds:
+                    if key not in data:
+                        raise KeyError(
+                            "generator data needs to contain fixed feature "
+                            f"column name `{key}`"
+                        )
                     f_data = data[key]
                     bounds = [f_data.min(), f_data.max()]
                     if bounds[1] - bounds[0] < 1e-8: