Merge pull request #328 from CITCOM-project/f-allian/chore

Enforce NetworkX 3.4

Author: f-allian

.github/workflows/ci-tests-drafts.yaml

@@ -22,6 +22,7 @@ jobs:
        python-version: ${{ matrix.python-version }}
     - name: Install dependencies
       run: |
+          python --version
           python -m pip install --upgrade pip
           pip install -e .
           pip install -e .[test]

causal_testing/testing/causal_test_case.py

@@ -47,6 +47,10 @@ def __init__(
         self.estimator = estimator
         if estimate_params is None:
             self.estimate_params = {}
+
+        else:
+            self.estimate_params = estimate_params
+
         self.effect = base_test_case.effect
 
         if effect_modifier_configuration:

pyproject.toml

@@ -18,7 +18,7 @@ dependencies = [
     "fitter~=1.7",
     "lifelines~=0.29.0",
     "lhsmdu~=1.1",
-    "networkx~=3.4",
+    "networkx>=3.4,<3.5",
     "numpy~=1.26",
     "pandas>=2.1",
     "scikit_learn~=1.4",

tests/testing_tests/test_causal_test_case.py

@@ -203,3 +203,45 @@ def test_execute_test_observational_linear_regression_estimator_squared_term(sel
         )
         causal_test_result = self.causal_test_case.execute_test(estimation_model)
         pd.testing.assert_series_equal(causal_test_result.test_value.value, pd.Series(4.0), atol=1)
+
+    def test_estimate_params_none(self):
+        """Check that estimate_params defaults to empty dict when None is passed into the estimator object"""
+        estimator = LinearRegressionEstimator(
+            base_test_case=self.base_test_case_A_C,
+            adjustment_set=set(),
+            control_value=0,
+            treatment_value=1,
+            formula="C ~ A + D",
+            df=self.df,
+        )
+        causal_test_case = CausalTestCase(
+            base_test_case=self.base_test_case_A_C,
+            expected_causal_effect=self.expected_causal_effect,
+            estimate_params=None,
+            estimator=estimator,
+            estimate_type="risk_ratio",
+        )
+        self.assertEqual(causal_test_case.estimate_params, {})
+        with self.assertRaises(ValueError):
+            causal_test_case.execute_test()
+
+    def test_estimate_params_with_formula(self):
+        """Ensure estimate params is handled correctly when a formula is passed into the estimator object"""
+        estimate_params = {"adjustment_config": {"D": 1}}
+        estimator = LinearRegressionEstimator(
+            base_test_case=self.base_test_case_A_C,
+            adjustment_set=set(),
+            control_value=0,
+            treatment_value=1,
+            formula="C ~ A + D",
+            df=self.df,
+        )
+        causal_test_case = CausalTestCase(
+            base_test_case=self.base_test_case_A_C,
+            expected_causal_effect=self.expected_causal_effect,
+            estimate_params=estimate_params,
+            estimate_type="risk_ratio",
+            estimator=estimator,
+        )
+        self.assertEqual(causal_test_case.estimate_params, estimate_params)
+        self.assertEqual(round(causal_test_case.execute_test().test_value.value[0], 3), 1.444)