Merge branch 'main' into pylint_refactoring

# Conflicts:
#	causal_testing/testing/causal_test_engine.py
#	tests/testing_tests/test_causal_test_outcome.py

Author: christopher-wild

.github/workflows/publish-to-pypi.yaml

@@ -3,7 +3,8 @@ name: Publish python PyPI
 on:
   push:
     tags:
-      - v0.0.0
+      - v*
+
 jobs:
   build-release:
     name: Build and publish PyPI
@@ -21,6 +22,8 @@ jobs:
           pip3 install .
           pip3 install .[pypi]
           pip3 install build
+          pip3 install setuptools --upgrade
+          pip3 install setuptools_scm
       - name: Build Package
         run: |
           python -m build --no-isolation

.github/workflows/publish-to-test-pypi.yaml

@@ -199,12 +199,12 @@ def _setup_test(self, causal_test_case: CausalTestCase, estimator: Estimator) ->
         treatment_var = causal_test_case.treatment_variable
         minimal_adjustment_set = minimal_adjustment_set - {treatment_var}
         estimation_model = estimator(
-            (treatment_var.name,),
-            causal_test_case.treatment_value,
-            causal_test_case.control_value,
-            minimal_adjustment_set,
-            (causal_test_case.outcome_variable.name,),
-            causal_test_engine.scenario_execution_data_df,
+            treatment=treatment_var.name,
+            treatment_value=causal_test_case.treatment_value,
+            control_value=causal_test_case.control_value,
+            adjustment_set=minimal_adjustment_set,
+            outcome=causal_test_case.outcome_variable.name,
+            df=causal_test_engine.scenario_execution_data_df,
             effect_modifiers=causal_test_case.effect_modifier_configuration,
         )
 

causal_testing/json_front/json_class.py

@@ -138,6 +138,36 @@ def __init__(self, dot_path: str = None, **attr):
         if not self.is_acyclic():
             raise nx.HasACycle("Invalid Causal DAG: contains a cycle.")
 
+    def check_iv_assumptions(self, treatment, outcome, instrument) -> bool:
+        """
+        Checks the three instrumental variable assumptions, raising a
+        ValueError if any are violated.
+
+        :return Boolean True if the three IV assumptions hold.
+        """
+        # (i) Instrument is associated with treatment
+        if nx.d_separated(self.graph, {instrument}, {treatment}, set()):
+            raise ValueError(f"Instrument {instrument} is not associated with treatment {treatment} in the DAG")
+
+        # (ii) Instrument does not affect outcome except through its potential effect on treatment
+        if not all([treatment in path for path in nx.all_simple_paths(self.graph, source=instrument, target=outcome)]):
+            raise ValueError(
+                f"Instrument {instrument} affects the outcome {outcome} other than through the treatment {treatment}"
+            )
+
+        # (iii) Instrument and outcome do not share causes
+        if any(
+            [
+                cause
+                for cause in self.graph.nodes
+                if list(nx.all_simple_paths(self.graph, source=cause, target=instrument))
+                and list(nx.all_simple_paths(self.graph, source=cause, target=outcome))
+            ]
+        ):
+            raise ValueError(f"Instrument {instrument} and outcome {outcome} share common causes")
+
+        return True
+
     def add_edge(self, u_of_edge: Node, v_of_edge: Node, **attr):
         """Add an edge to the causal DAG.
 

causal_testing/specification/causal_dag.py

@@ -86,11 +86,11 @@ def execute_test_suite(self, test_suite: CausalTestSuite) -> list[CausalTestResu
 
                 for test in tests:
                     estimator = estimator_class(
-                        (test.treatment_variable.name,),
+                        test.treatment_variable.name,
                         test.treatment_value,
                         test.control_value,
                         minimal_adjustment_set,
-                        (test.outcome_variable.name,),
+                        test.outcome_variable.name,
                     )
                     if estimator.df is None:
                         estimator.df = self.scenario_execution_data_df

causal_testing/testing/causal_test_engine.py

@@ -68,22 +68,22 @@ def to_dict(self):
             "adjustment_set": self.adjustment_set,
             "test_value": self.test_value,
         }
-        if self.confidence_intervals:
+        if self.confidence_intervals and all(self.confidence_intervals):
             base_dict["ci_low"] = min(self.confidence_intervals)
             base_dict["ci_high"] = max(self.confidence_intervals)
         return base_dict
 
     def ci_low(self):
         """Return the lower bracket of the confidence intervals."""
-        if not self.confidence_intervals:
-            return None
-        return min(self.confidence_intervals)
+        if self.confidence_intervals and all(self.confidence_intervals):
+            return min(self.confidence_intervals)
+        return None
 
     def ci_high(self):
         """Return the higher bracket of the confidence intervals."""
-        if not self.confidence_intervals:
-            return None
-        return max(self.confidence_intervals)
+        if self.confidence_intervals and all(self.confidence_intervals):
+            return max(self.confidence_intervals)
+        return None
 
     def summary(self):
         """Summarise the causal test result as an intuitive sentence."""