test causal dag patch

Author: jmafoster1

causal_testing/specification/causal_dag.py

@@ -558,7 +558,7 @@ def identification(self, base_test_case: BaseTestCase, scenario: Scenario = None
         estimate as opposed to a purely associational estimate.
         """
         if self.ignore_cycles:
-            return self.graph.predecessors(base_test_case.treatment_variable.name)
+            return set(self.graph.predecessors(base_test_case.treatment_variable.name))
         minimal_adjustment_sets = []
         if base_test_case.effect == "total":
             minimal_adjustment_sets = self.enumerate_minimal_adjustment_sets(
@@ -578,7 +578,7 @@ def identification(self, base_test_case: BaseTestCase, scenario: Scenario = None
             return set()
 
         minimal_adjustment_set = min(minimal_adjustment_sets, key=len)
-        return minimal_adjustment_set
+        return set(minimal_adjustment_set)
 
     def to_dot_string(self) -> str:
         """Return a string of the DOT representation of the causal DAG.

tests/specification_tests/test_causal_dag.py

@@ -85,7 +85,6 @@ def setUp(self) -> None:
     def test_valid_causal_dag(self):
         """Test whether the Causal DAG is valid."""
         causal_dag = CausalDAG(self.dag_dot_path)
-        print(causal_dag)
         assert list(causal_dag.nodes) == ["A", "B", "C", "D"] and list(causal_dag.edges) == [
             ("A", "B"),
             ("B", "C"),
@@ -127,6 +126,11 @@ def setUp(self) -> None:
     def test_invalid_causal_dag(self):
         self.assertRaises(nx.HasACycle, CausalDAG, self.dag_dot_path)
 
+    def test_ignore_cycles(self):
+        dag = CausalDAG(self.dag_dot_path, ignore_cycles=True)
+        base_test_case = BaseTestCase(Output("B", float), Output("C", float))
+        self.assertEqual(dag.identification(base_test_case), {"A"})
+
     def tearDown(self) -> None:
         shutil.rmtree(self.temp_dir_path)
 

tests/testing_tests/test_metamorphic_relations.py

@@ -55,7 +55,7 @@ def test_should_not_cause_json_stub(self):
                 "estimate_type": "coefficient",
                 "estimator": "LinearRegressionEstimator",
                 "expected_effect": {"Z": "NoEffect"},
-                "mutations": ["X1"],
+                "treatment_variable": "X1",
                 "name": "X1 _||_ Z",
                 "formula": "Z ~ X1",
                 "alpha": 0.05,
@@ -78,7 +78,7 @@ def test_should_cause_json_stub(self):
                 "estimator": "LinearRegressionEstimator",
                 "expected_effect": {"Z": "SomeEffect"},
                 "formula": "Z ~ X1",
-                "mutations": ["X1"],
+                "treatment_variable": "X1",
                 "name": "X1 --> Z",
                 "skip": True,
             },