Strip Unused Dependencies

causal_testing/specification/variable.py

@@ -5,7 +5,6 @@
 from collections.abc import Callable
 from typing import TypeVar
 
-import lhsmdu
 from pandas import DataFrame
 from scipy.stats._distn_infrastructure import rv_generic
 
@@ -38,19 +37,6 @@ def __init__(self, name: str, datatype: T, distribution: rv_generic = None, hidd
     def __repr__(self):
         return f"{self.typestring()}: {self.name}::{self.datatype.__name__}"
 
-    def sample(self, n_samples: int) -> [T]:
-        """Generate a Latin Hypercube Sample of size n_samples according to the
-        Variable's distribution.
-
-        :param int n_samples: The number of samples to generate.
-        :return: A list of samples
-        :rtype: List[T]
-
-        """
-        assert self.distribution is not None, "Sampling requires a distribution to be specified."
-        lhs = lhsmdu.sample(1, n_samples).tolist()[0]
-        return lhsmdu.inverseTransformSample(self.distribution, lhs).tolist()
-
     def typestring(self) -> str:
         """Return the type of the Variable, e.g. INPUT, or OUTPUT. Note that
         this is NOT the datatype (int, str, etc.).

causal_testing/testing/metamorphic_relation.py

@@ -39,14 +39,14 @@ class ShouldCause(MetamorphicRelation):
 
     def to_json_stub(
         self,
-        skip: bool = True,
+        skip: bool = False,
         estimate_type: str = "coefficient",
         effect_type: str = "direct",
         estimator: str = "LinearRegressionEstimator",
     ) -> dict:
         """
         Convert to a JSON frontend stub string for user customisation.
-        :param skip: Whether to skip the test
+        :param skip: Whether to skip the test (default False).
         :param effect_type: The type of causal effect to consider (total or direct)
         :param estimate_type: The estimate type to use when evaluating tests
         :param estimator: The name of the estimator class to use when evaluating the test
@@ -77,14 +77,14 @@ class ShouldNotCause(MetamorphicRelation):
 
     def to_json_stub(
         self,
-        skip: bool = True,
+        skip: bool = False,
         estimate_type: str = "coefficient",
         effect_type: str = "direct",
         estimator: str = "LinearRegressionEstimator",
     ) -> dict:
         """
         Convert to a JSON frontend stub string for user customisation.
-        :param skip: Whether to skip the test
+        :param skip: Whether to skip the test (default False).
         :param effect_type: The type of causal effect to consider (total or direct)
         :param estimate_type: The estimate type to use when evaluating tests
         :param estimator: The name of the estimator class to use when evaluating the test
@@ -244,6 +244,10 @@ def generate_causal_tests(
         if len(list(causal_dag.predecessors(relation.base_test_case.outcome_variable))) > 0
     ]
 
+    logger.warning("The skip parameter is hard-coded to False during test generation for better integration with the "
+                   "causal testing component (python -m causal_testing test ...)"
+                   "Please carefully review the generated tests and decide which to skip.")
+
     logger.info(f"Generated {len(tests)} tests. Saving to {output_path}.")
     with open(output_path, "w", encoding="utf-8") as f:
         json.dump({"tests": tests}, f, indent=2)

pyproject.toml

@@ -15,9 +15,7 @@ requires-python = ">=3.10"
 license = { text = "MIT" }
 keywords = ["causal inference", "verification"]
 dependencies = [
-    "fitter~=1.7",
     "lifelines~=0.29.0",
-    "lhsmdu~=1.1",
     "networkx>=3.4,<3.5",
     "numpy~=1.26",
     "pandas>=2.1",

tests/specification_tests/test_variable.py

@@ -13,10 +13,6 @@ class TestVariable(unittest.TestCase):
     def setUp(self) -> None:
         pass
 
-    def test_sample_flakey(self):
-        ip = Input("ip", float, norm)
-        self.assertGreater(kstest(ip.sample(10), norm.cdf).pvalue, 0.95)
-
     def test_typestring(self):
         class Var(Variable):
             pass

tests/testing_tests/test_metamorphic_relations.py

@@ -62,7 +62,7 @@ def test_should_not_cause_json_stub(self):
                 "name": "X1 _||_ Z",
                 "formula": "Z ~ X1",
                 "alpha": 0.05,
-                "skip": True,
+                "skip": False,
             },
         )
 
@@ -86,7 +86,7 @@ def test_should_not_cause_logistic_json_stub(self):
                 "name": "X1 _||_ Z",
                 "formula": "Z ~ X1",
                 "alpha": 0.05,
-                "skip": True,
+                "skip": False,
             },
         )
 
@@ -107,7 +107,7 @@ def test_should_cause_json_stub(self):
                 "formula": "Z ~ X1",
                 "treatment_variable": "X1",
                 "name": "X1 --> Z",
-                "skip": True,
+                "skip": False,
             },
         )
 
@@ -120,7 +120,7 @@ def test_should_cause_logistic_json_stub(self):
         should_cause_mr = ShouldCause(BaseTestCase("X1", "Z"), adj_set)
         self.assertEqual(
             should_cause_mr.to_json_stub(
-                effect_type="total", estimate_type="unit_odds_ratio", estimator="LogisticRegressionEstimator", skip=True
+                effect_type="total", estimate_type="unit_odds_ratio", estimator="LogisticRegressionEstimator", skip=False
             ),
             {
                 "effect": "total",
@@ -130,7 +130,7 @@ def test_should_cause_logistic_json_stub(self):
                 "formula": "Z ~ X1",
                 "treatment_variable": "X1",
                 "name": "X1 --> Z",
-                "skip": True,
+                "skip": False,
             },
         )
 
@@ -263,7 +263,7 @@ def test_generate_causal_tests_ignore_cycles(self):
                 tests = json.load(f)
             expected = list(
                 map(
-                    lambda x: x.to_json_stub(skip=True),
+                    lambda x: x.to_json_stub(skip=False),
                     filter(
                         lambda relation: len(list(dcg.predecessors(relation.base_test_case.outcome_variable))) > 0,
                         relations,
@@ -282,7 +282,7 @@ def test_generate_causal_tests(self):
                 tests = json.load(f)
             expected = list(
                 map(
-                    lambda x: x.to_json_stub(skip=True),
+                    lambda x: x.to_json_stub(skip=False),
                     filter(
                         lambda relation: len(list(dag.predecessors(relation.base_test_case.outcome_variable))) > 0,
                         relations,