Switch strict meaning in validate_number_positive

metalearners/_utils.py

@@ -1,7 +1,6 @@
 # # Copyright (c) QuantCo 2024-2024
 # # SPDX-License-Identifier: BSD-3-Clause
 
-import operator
 from collections.abc import Callable
 from inspect import signature
 from operator import le, lt
@@ -66,14 +65,22 @@ def validate_all_vectors_same_index(*args: Vector) -> None:
 
 
 def validate_number_positive(
-    value: int | float, name: str, strict: bool = False
+    value: int | float, name: str, strict: bool = True
 ) -> None:
+    """Validates that a number is positive.
+
+    If ``strict = True`` then it validates that the number is strictly positive.
+    """
     if strict:
-        comparison = operator.lt
+        if value <= 0:
+            raise ValueError(
+                f"{name} was expected to be strictly positive but was {value}."
+            )
     else:
-        comparison = operator.le
-    if comparison(value, 0):
-        raise ValueError(f"{name} was expected to be positive but was {value}.")
+        if value < 0:
+            raise ValueError(
+                f"{name} was expected to be positive or zero but was {value}."
+            )
 
 
 def check_propensity_score(

metalearners/cross_fit_estimator.py

@@ -56,7 +56,7 @@ def _validate_data_match_prior_split(
 ) -> None:
     """Validate whether the previous test_indices and the passed data are based on the
     same number of observations."""
-    validate_number_positive(n_observations, "n_observations", strict=False)
+    validate_number_positive(n_observations, "n_observations", strict=True)
     if test_indices is None:
         return
     expected_n_observations = sum(len(x) for x in test_indices)

tests/test_cross_fit_estimator.py

@@ -223,7 +223,9 @@ def test_crossfitestimator_n_folds_1(rng, sample_size):
 )
 def test_validate_data_match(n_observations, test_indices, success):
     if n_observations < 1:
-        with pytest.raises(ValueError, match="was expected to be positive"):
+        with pytest.raises(
+            ValueError, match=r"was expected to be (strictly )?positive"
+        ):
             _validate_data_match_prior_split(n_observations, test_indices)
         return
     if success: