move test

Author: SimonBlanke

src/hyperactive/base/tests/test_endtoend.py

@@ -47,3 +47,51 @@ def test_endtoend_hillclimbing():
     assert isinstance(best_params, dict), "Best parameters should be a dictionary"
     assert "C" in best_params, "Best parameters should contain 'C'"
     assert "gamma" in best_params, "Best parameters should contain 'gamma'"
+
+
+def test_endtoend_lightgbm():
+    """Test end-to-end usage of HillClimbing optimizer with LightGBM experiment."""
+    from skbase.utils.dependencies import _check_soft_dependencies
+
+    if not _check_soft_dependencies("lightgbm", severity="none"):
+        return None
+
+    # 1. define the experiment
+    from lightgbm import LGBMClassifier
+    from sklearn.datasets import load_iris
+
+    from hyperactive.experiment.integrations import LightGBMExperiment
+
+    X, y = load_iris(return_X_y=True)
+
+    lgbm_exp = LightGBMExperiment(
+        estimator=LGBMClassifier(n_estimators=10, verbosity=-1),
+        X=X,
+        y=y,
+        cv=2,
+    )
+
+    # 2. set up the HillClimbing optimizer
+    import numpy as np
+
+    from hyperactive.opt import HillClimbing
+
+    hillclimbing_config = {
+        "search_space": {
+            "n_estimators": np.array([5, 10, 20]),
+            "max_depth": np.array([2, 3, 5]),
+        },
+        "n_iter": 10,
+    }
+    hill_climbing = HillClimbing(**hillclimbing_config, experiment=lgbm_exp)
+
+    # 3. run the HillClimbing optimizer
+    hill_climbing.solve()
+
+    best_params = hill_climbing.best_params_
+    assert best_params is not None, "Best parameters should not be None"
+    assert isinstance(best_params, dict), "Best parameters should be a dictionary"
+    assert (
+        "n_estimators" in best_params
+    ), "Best parameters should contain 'n_estimators'"
+    assert "max_depth" in best_params, "Best parameters should contain 'max_depth'"