Refactor BaseCausalTest to BaseTestCase

Author: christopher-wild

causal_testing/generation/abstract_causal_test_case.py

@@ -9,7 +9,7 @@
 from causal_testing.specification.variable import Variable
 from causal_testing.testing.causal_test_case import CausalTestCase
 from causal_testing.testing.causal_test_outcome import CausalTestOutcome
-from causal_testing.testing.base_causal_test import BaseCausalTest
+from causal_testing.testing.base_test_case import BaseTestCase
 
 logger = logging.getLogger(__name__)
 
@@ -110,10 +110,10 @@ def _generate_concrete_tests(
                 )
             model = optimizer.model()
 
-            base_causal_test = BaseCausalTest(self.treatment_variables, list(self.expected_causal_effect.keys())[0])
+            base_test_case = BaseTestCase(self.treatment_variables, list(self.expected_causal_effect.keys())[0])
 
             concrete_test = CausalTestCase(
-                base_causal_test=base_causal_test,
+                base_test_case=base_test_case,
                 control_value=self.treatment_variables.cast(model[self.treatment_variables.z3]),
                 treatment_value=self.treatment_variables.cast(
                     model[self.scenario.treatment_variables[self.treatment_variables.name].z3]

causal_testing/json_front/json_class.py

@@ -205,7 +205,7 @@ def _setup_test(self, causal_test_case: CausalTestCase, estimator: Estimator) ->
         """
         data_collector = ObservationalDataCollector(self.modelling_scenario, self.data_path)
         causal_test_engine = CausalTestEngine(self.causal_specification, data_collector, index_col=0)
-        minimal_adjustment_set = self.causal_specification.causal_dag.identification(causal_test_case.base_causal_test)
+        minimal_adjustment_set = self.causal_specification.causal_dag.identification(causal_test_case.base_test_case)
         treatment_vars = list(causal_test_case.treatment_input_configuration)
         minimal_adjustment_set = minimal_adjustment_set - {v.name for v in treatment_vars}
         estimation_model = estimator(

causal_testing/testing/base_causal_test.py renamed to causal_testing/testing/base_test_case.py

@@ -3,7 +3,7 @@
 
 
 @dataclass(frozen=True)
-class BaseCausalTest:
+class BaseTestCase:
     """
     A base causal test case represents the relationship of an edge on a causal DAG.
     """

causal_testing/testing/causal_test_case.py

@@ -3,7 +3,7 @@
 
 from causal_testing.specification.variable import Variable
 from causal_testing.testing.causal_test_outcome import CausalTestOutcome
-from causal_testing.testing.base_causal_test import BaseCausalTest
+from causal_testing.testing.base_test_case import BaseTestCase
 
 logger = logging.getLogger(__name__)
 
@@ -18,7 +18,7 @@ class CausalTestCase:
 
     def __init__(
         self,
-        base_causal_test: BaseCausalTest,
+        base_test_case: BaseTestCase,
         expected_causal_effect: CausalTestOutcome,
         control_value: Any,
         treatment_value: Any = None,
@@ -36,13 +36,13 @@ def __init__(
         :param treatment_input_configuration: The input configuration representing the treatment values of the treatment
         variables. That is, the input configuration *after* applying the intervention.
         """
-        self.base_causal_test = base_causal_test
-        self.control_input_configuration = {base_causal_test.treatment_variable: control_value}
+        self.base_test_case = base_test_case
+        self.control_input_configuration = {base_test_case.treatment_variable: control_value}
         self.expected_causal_effect = expected_causal_effect
-        self.outcome_variable = base_causal_test.outcome_variable
-        self.treatment_input_configuration = {base_causal_test.treatment_variable: treatment_value}
+        self.outcome_variable = base_test_case.outcome_variable
+        self.treatment_input_configuration = {base_test_case.treatment_variable: treatment_value}
         self.estimate_type = estimate_type
-        self.effect = base_causal_test.effect
+        self.effect = base_test_case.effect
         if effect_modifier_configuration:
             self.effect_modifier_configuration = effect_modifier_configuration
         else:

causal_testing/testing/causal_test_engine.py

@@ -7,7 +7,7 @@
 from causal_testing.testing.causal_test_case import CausalTestCase
 from causal_testing.testing.causal_test_outcome import CausalTestResult
 from causal_testing.testing.estimators import Estimator
-from causal_testing.testing.base_causal_test import BaseCausalTest
+from causal_testing.testing.base_test_case import BaseTestCase
 from causal_testing.testing.causal_test_suite import CausalTestSuite
 
 logger = logging.getLogger(__name__)
@@ -53,8 +53,7 @@ def __init__(self, causal_specification: CausalSpecification, data_collector: Da
         self.data_collector = data_collector
         self.scenario_execution_data_df = self.data_collector.collect_data(**kwargs)
 
-    def execute_test_suite(
-            self, test_suite: CausalTestSuite) -> list[CausalTestResult]:
+    def execute_test_suite(self, test_suite: CausalTestSuite) -> list[CausalTestResult]:
 
         """Execute a suite of causal tests and return the results in a list
         :param test_suite: CasualTestSuite object
@@ -75,7 +74,7 @@ def execute_test_suite(
             minimal_adjustment_set = minimal_adjustment_set - set(edge.outcome_variable.name)
 
             variables_for_positivity = (
-                    list(minimal_adjustment_set) + [edge.treatment_variable.name] + [edge.outcome_variable.name]
+                list(minimal_adjustment_set) + [edge.treatment_variable.name] + [edge.outcome_variable.name]
             )
             if self._check_positivity_violation(variables_for_positivity):
                 # TODO: We should allow users to continue because positivity can be overcome with parametric models
@@ -110,7 +109,7 @@ def execute_test_suite(
         return test_suite_results
 
     def execute_test(
-            self, estimator: type(Estimator), causal_test_case: CausalTestCase, estimate_type: str = "ate"
+        self, estimator: type(Estimator), causal_test_case: CausalTestCase, estimate_type: str = "ate"
     ) -> CausalTestResult:
         """Execute a causal test case and return the causal test result.
 
@@ -139,7 +138,7 @@ def execute_test(
 
         logger.info("treatments: %s", treatments)
         logger.info("outcomes: %s", outcome_variable)
-        minimal_adjustment_set = self.causal_dag.identification(BaseCausalTest(treatment_variable, outcome_variable))
+        minimal_adjustment_set = self.causal_dag.identification(BaseTestCase(treatment_variable, outcome_variable))
         minimal_adjustment_set = minimal_adjustment_set - {v.name for v in causal_test_case.control_input_configuration}
         minimal_adjustment_set = minimal_adjustment_set - set(outcome_variable.name)
         assert all(

causal_testing/testing/causal_test_suite.py

@@ -9,12 +9,12 @@ class CausalTestSuite:
     """
 
     def __init__(
-            self,
+        self,
     ):
         self.test_suite = {}
 
     def add_test_object(self, base_test_case, causal_test_case_list, estimators, estimate_type):
-        test_object = {'tests': causal_test_case_list, 'estimators': estimators, 'estimate_type': estimate_type}
+        test_object = {"tests": causal_test_case_list, "estimators": estimators, "estimate_type": estimate_type}
         self.test_suite[base_test_case] = test_object
 
     def get_single_test_object(self, base_test_case):

examples/lr91/causal_test_max_conductances.py

@@ -10,7 +10,7 @@
 from causal_testing.testing.causal_test_outcome import Positive, Negative, NoEffect
 from causal_testing.testing.causal_test_engine import CausalTestEngine
 from causal_testing.testing.estimators import LinearRegressionEstimator
-from causal_testing.testing.base_causal_test import BaseCausalTest
+from causal_testing.testing.base_test_case import BaseTestCase
 from matplotlib.pyplot import rcParams
 
 # Uncommenting the code below will make all graphs publication quality but requires a suitable latex installation
@@ -110,9 +110,9 @@ def effects_on_APD90(observational_data_path, treatment_var, control_val, treatm
 
     # 5. Create a causal specification from the scenario and causal DAG
     causal_specification = CausalSpecification(scenario, causal_dag)
-    base_test_case = BaseCausalTest(treatment_var, apd90)
+    base_test_case = BaseTestCase(treatment_var, apd90)
     # 6. Create a causal test case
-    causal_test_case = CausalTestCase(base_causal_test=base_test_case,
+    causal_test_case = CausalTestCase(base_test_case=base_test_case,
                                       expected_causal_effect=expected_causal_effect,
                                       control_value=control_val,
                                       treatment_value=treatment_val)

examples/lr91/causal_test_max_conductances_test_suite.py

@@ -10,7 +10,7 @@
 from causal_testing.testing.causal_test_outcome import Positive, Negative, NoEffect
 from causal_testing.testing.causal_test_engine import CausalTestEngine
 from causal_testing.testing.estimators import LinearRegressionEstimator
-from causal_testing.testing.base_causal_test import BaseCausalTest
+from causal_testing.testing.base_test_case import BaseTestCase
 from causal_testing.testing.causal_test_suite import CausalTestSuite
 from matplotlib.pyplot import rcParams
 
@@ -63,7 +63,7 @@ def causal_testing_sensitivity_analysis():
 
     for conductance_param, mean_and_oracle in conductance_means.items():
         treatment_variable = Input(conductance_param, float)
-        base_test_case = BaseCausalTest(treatment_variable, outcome_variable)
+        base_test_case = BaseTestCase(treatment_variable, outcome_variable)
         test_list = []
         control_value = 0.5
         mean, oracle = mean_and_oracle

tests/testing_tests/test_causal_test_case.py

@@ -6,7 +6,7 @@
 from causal_testing.specification.causal_dag import CausalDAG
 from causal_testing.testing.causal_test_case import CausalTestCase
 from causal_testing.testing.causal_test_outcome import ExactValue
-from causal_testing.testing.base_causal_test import BaseCausalTest
+from causal_testing.testing.base_test_case import BaseTestCase
 
 class TestCausalTestEngineObservational(unittest.TestCase):
     """ Test the CausalTestEngine workflow using observational data.
@@ -34,9 +34,9 @@ def setUp(self) -> None:
 
         # 3. Create an intervention and causal test case
         self.expected_causal_effect = ExactValue(4)
-        self.base_causal_test = BaseCausalTest(A, C)
+        self.base_test_case = BaseTestCase(A, C)
         self.causal_test_case = CausalTestCase(
-            base_causal_test=self.base_causal_test,
+            base_test_case=self.base_test_case,
             expected_causal_effect=self.expected_causal_effect,
             control_value=0,
             treatment_value=1