Confidence intervals through inheritence

Author: jmafoster1

causal_testing/testing/causal_test_outcome.py

@@ -22,7 +22,35 @@ def __str__(self) -> str:
         return type(self).__name__
 
 
-class ExactValue(CausalTestOutcome):
+class SomeEffect(CausalTestOutcome):
+    """An extension of TestOutcome representing that the expected causal effect should not be zero."""
+
+    def apply(self, res: CausalTestResult) -> bool:
+        if res.test_value.type == "ate":
+            return (0 < res.ci_low() < res.ci_high()) or (res.ci_low() < res.ci_high() < 0)
+        if res.test_value.type == "risk_ratio":
+            return (1 < res.ci_low() < res.ci_high()) or (res.ci_low() < res.ci_high() < 1)
+        raise ValueError(f"Test Value type {res.test_value.type} is not valid for this TestOutcome")
+
+    def __str__(self):
+        return "Changed"
+
+
+class NoEffect(CausalTestOutcome):
+    """An extension of TestOutcome representing that the expected causal effect should be zero."""
+
+    def apply(self, res: CausalTestResult) -> bool:
+        if res.test_value.type == "ate":
+            return (res.ci_low() < 0 < res.ci_high()) or (abs(res.test_value.value) < 1e-10)
+        if res.test_value.type == "risk_ratio":
+            return (res.ci_low() < 1 < res.ci_high()) or np.isclose(res.test_value.value, 1.0, atol=1e-10)
+        raise ValueError(f"Test Value type {res.test_value.type} is not valid for this TestOutcome")
+
+    def __str__(self):
+        return "Unchanged"
+
+
+class ExactValue(SomeEffect):
     """An extension of TestOutcome representing that the expected causal effect should be a specific value."""
 
     def __init__(self, value: float, tolerance: float = None):
@@ -33,57 +61,32 @@ def __init__(self, value: float, tolerance: float = None):
             self.tolerance = tolerance
 
     def apply(self, res: CausalTestResult) -> bool:
+        super().apply()
         return np.isclose(res.test_value.value, self.value, atol=self.tolerance)
 
     def __str__(self):
         return f"ExactValue: {self.value}±{self.tolerance}"
 
 
-class Positive(CausalTestOutcome):
+class Positive(SomeEffect):
     """An extension of TestOutcome representing that the expected causal effect should be positive."""
 
     def apply(self, res: CausalTestResult) -> bool:
+        super().apply()
         if res.test_value.type == "ate":
             return res.test_value.value > 0
         if res.test_value.type == "risk_ratio":
             return res.test_value.value > 1
         raise ValueError(f"Test Value type {res.test_value.type} is not valid for this TestOutcome")
 
 
-class Negative(CausalTestOutcome):
+class Negative(SomeEffect):
     """An extension of TestOutcome representing that the expected causal effect should be negative."""
 
     def apply(self, res: CausalTestResult) -> bool:
+        super().apply()
         if res.test_value.type == "ate":
             return res.test_value.value < 0
         if res.test_value.type == "risk_ratio":
             return res.test_value.value < 1
         raise ValueError(f"Test Value type {res.test_value.type} is not valid for this TestOutcome")
-
-
-class SomeEffect(CausalTestOutcome):
-    """An extension of TestOutcome representing that the expected causal effect should not be zero."""
-
-    def apply(self, res: CausalTestResult) -> bool:
-        if res.test_value.type == "ate":
-            return (0 < res.ci_low() < res.ci_high()) or (res.ci_low() < res.ci_high() < 0)
-        if res.test_value.type == "risk_ratio":
-            return (1 < res.ci_low() < res.ci_high()) or (res.ci_low() < res.ci_high() < 1)
-        raise ValueError(f"Test Value type {res.test_value.type} is not valid for this TestOutcome")
-
-    def __str__(self):
-        return "Changed"
-
-
-class NoEffect(CausalTestOutcome):
-    """An extension of TestOutcome representing that the expected causal effect should be zero."""
-
-    def apply(self, res: CausalTestResult) -> bool:
-        if res.test_value.type == "ate":
-            return (res.ci_low() < 0 < res.ci_high()) or (abs(res.test_value.value) < 1e-10)
-        if res.test_value.type == "risk_ratio":
-            return (res.ci_low() < 1 < res.ci_high()) or np.isclose(res.test_value.value, 1.0, atol=1e-10)
-        raise ValueError(f"Test Value type {res.test_value.type} is not valid for this TestOutcome")
-
-    def __str__(self):
-        return "Unchanged"