Correct LPI importance tests

Author: Sarah Krebs

CHANGELOG.md

@@ -21,6 +21,8 @@
 - Fix errors due to changing inputs before runselection (#64).
 - For fANOVA, remove constant hyperparameters from configspace (#9).
 - For PCP, show hyperparameters with highest importance closest to the cost (i.e. right).
+- Add init files to all test directories.
+- Correct LPI importance tests.
 
 ## Version-Updates
 - Black version from 23.1.0 to 23.3.0

tests/test_evaluators/test_lpi.py

@@ -2,13 +2,13 @@
 
 from deepcave.evaluators.lpi import LPI as Evaluator
 from deepcave.runs import AbstractRun
-from deepcave.runs.converters.smac3v1 import SMAC3v1Run
+from deepcave.runs.converters.smac3v2 import SMAC3v2Run
 
 
 class TestLPI(unittest.TestCase):
     def setUp(self):
         # Initiate run here
-        self.run: AbstractRun = SMAC3v1Run.from_path("logs/SMAC3v1/mlp/run_1")
+        self.run: AbstractRun = SMAC3v2Run.from_path("logs/SMAC3v2/mlp/run_1")
         self.hp_names = self.run.configspace.get_hyperparameter_names()
         self.evaluator = Evaluator(self.run)
 
@@ -17,10 +17,28 @@ def test(self):
         objective = self.run.get_objective(0)
 
         # Calculate
-        self.evaluator.calculate(objective, budget)
-        importance_dict = self.evaluator.get_importances(self.hp_names)
+        self.evaluator.calculate(objective, budget, seed=0)
+        importances = self.evaluator.get_importances(self.hp_names)
 
-        print(importance_dict)
+        self.evaluator.calculate(objective, budget, seed=42)
+        importances2 = self.evaluator.get_importances(self.hp_names)
+
+        # Different seed: Different results
+        assert importances["batch_size"][1] != importances2["batch_size"][1]
+
+    def test_seed(self):
+        budget = self.run.get_budget(0)
+        objective = self.run.get_objective(0)
+
+        # Calculate
+        self.evaluator.calculate(objective, budget, seed=0)
+        importances = self.evaluator.get_importances(self.hp_names)
+
+        self.evaluator.calculate(objective, budget, seed=0)
+        importances2 = self.evaluator.get_importances(self.hp_names)
+
+        # Same seed: Same results
+        assert importances["batch_size"][1] == importances2["batch_size"][1]
 
 
 if __name__ == "__main__":