Update tests

Author: christopher-wild

tests/data_collection_tests/test_observational_data_collector.py

@@ -38,18 +38,18 @@ class Color(Enum):
 
     def test_not_all_variables_in_data(self):
         scenario = Scenario({self.X1, self.X2, self.X3, self.X4})
-        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df_path)
+        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df)
         self.assertRaises(IndexError, observational_data_collector.collect_data)
 
     def test_all_variables_in_data(self):
         scenario = Scenario({self.X1, self.X2, self.X3, self.Y1, self.Y2})
-        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df_path)
+        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df)
         df = observational_data_collector.collect_data(index_col=0)
         assert df.equals(self.observational_df), f"\n{df}\nwas not equal to\n{self.observational_df}"
 
     def test_data_constraints(self):
         scenario = Scenario({self.X1, self.X2, self.X3, self.Y1, self.Y2}, {self.X1.z3 > 2})
-        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df_path)
+        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df)
         df = observational_data_collector.collect_data(index_col=0)
         expected = self.observational_df.loc[[2, 3]]
         assert df.equals(expected), f"\n{df}\nwas not equal to\n{expected}"
@@ -60,7 +60,7 @@ def populate_m(data):
 
         meta = Meta("M", int, populate_m)
         scenario = Scenario({self.X1, meta})
-        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df_path)
+        observational_data_collector = ObservationalDataCollector(scenario, self.observational_df)
         data = observational_data_collector.collect_data()
         assert all((m == 2 * x1 for x1, m in zip(data["X1"], data["M"])))
 

tests/json_front_tests/test_json_class.py

@@ -28,7 +28,7 @@ def setUp(self) -> None:
         test_data_dir_path = Path("tests/resources/data")
         self.json_path = str(test_data_dir_path / json_file_name)
         self.dag_path = str(test_data_dir_path / dag_file_name)
-        self.data_path = str(test_data_dir_path / data_file_name)
+        self.data_path = [str(test_data_dir_path / data_file_name)]
         self.json_class = JsonUtility("logs.log")
         self.example_distribution = scipy.stats.uniform(1, 10)
         self.input_dict_list = [{"name": "test_input", "type": float, "distribution": self.example_distribution}]
@@ -40,7 +40,7 @@ def setUp(self) -> None:
     def test_setting_paths(self):
         self.assertEqual(self.json_class.paths.json_path, Path(self.json_path))
         self.assertEqual(self.json_class.paths.dag_path, Path(self.dag_path))
-        self.assertEqual(self.json_class.paths.data_path, Path(self.data_path))
+        self.assertEqual(self.json_class.paths.data_paths, [Path(self.data_path[0])]) # Needs to be list of Paths
 
     def test_set_inputs(self):
         ctf_input = [Input("test_input", float, self.example_distribution)]
@@ -61,7 +61,7 @@ def test_set_metas(self):
 
     def test_argparse(self):
         args = self.json_class.get_args(["--data_path=data.csv", "--dag_path=dag.dot", "--json_path=tests.json"])
-        self.assertEqual(args.data_path, "data.csv")
+        self.assertEqual(args.data_path, ["data.csv"])
         self.assertEqual(args.dag_path, "dag.dot")
         self.assertEqual(args.json_path, "tests.json")
 

tests/testing_tests/test_causal_test_engine.py

@@ -59,7 +59,7 @@ def setUp(self) -> None:
 
         # 5. Create observational data collector
         # Obsolete?
-        self.data_collector = ObservationalDataCollector(self.scenario, self.observational_data_csv_path)
+        self.data_collector = ObservationalDataCollector(self.scenario, df)
 
         # 5. Create causal test engine
         self.causal_test_engine = CausalTestEngine(self.causal_specification, self.data_collector)

tests/testing_tests/test_causal_test_suite.py

@@ -40,9 +40,7 @@ def setUp(self) -> None:
         df = pd.DataFrame({"D": list(np.random.normal(60, 10, 1000))})  # D = exogenous
         df["A"] = [1 if d > 50 else 0 for d in df["D"]]
         df["C"] = df["D"] + (4 * (df["A"] + 2))  # C = (4*(A+2)) + D
-        self.observational_data_csv_path = os.path.join(temp_dir_path, "observational_data.csv")
-        df.to_csv(self.observational_data_csv_path, index=False)
-
+        self.df = df
         self.causal_dag = CausalDAG(dag_dot_path)
 
         # 3. Specify data structures required for test suite
@@ -126,6 +124,6 @@ def create_causal_test_engine(self):
         """
         causal_specification = CausalSpecification(self.scenario, self.causal_dag)
 
-        data_collector = ObservationalDataCollector(self.scenario, self.observational_data_csv_path)
+        data_collector = ObservationalDataCollector(self.scenario, self.df)
         causal_test_engine = CausalTestEngine(causal_specification, data_collector)
         return causal_test_engine