deprecation warning added

Author: TonyKatkov89

hypex/aa.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import warnings
 from typing import Any, Iterable
 
 from .analyzers.aa import AAScoreAnalyzer, OneAAStatAnalyzer
@@ -199,7 +200,17 @@ def __init__(
         random_states: Iterable[int] | None = None,
         equal_variance: bool | None = None,
         groups_sizes: list[float] | None = None,
+        **kwargs,
     ):
+        if "t_test_equal_var" in kwargs:
+            warnings.warn(
+                "t_test_equal_var is deprecated and will be removed in a future version. "
+                "Use equal_variance instead.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            if equal_variance is None:
+                equal_variance = kwargs.pop("t_test_equal_var")
         if n_iterations is None:
             if precision_mode:
                 n_iterations = 2000

hypex/ab.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import warnings
 from typing import Literal
 
 from .analyzers.ab import ABAnalyzer
@@ -148,6 +149,7 @@ def __init__(
         cuped_features: dict[str, str] | None = None,
         cupac_models: str | list[str] | None = None,
         enable_cupac: bool = False,
+        **kwargs,
     ):
         """
         Args:
@@ -158,6 +160,15 @@ def __init__(
             cupac_models: str | list[str] — model name (e.g. 'linear', 'ridge', 'lasso', 'catboost') or list of model names to try. If None, all available models will be tried and the best will be selected by variance reduction.
             enable_cupac: bool — Enable CUPAC variance reduction. CUPAC configuration is extracted from dataset.features_mapping.
         """
+        if "t_test_equal_var" in kwargs:
+            warnings.warn(
+                "t_test_equal_var is deprecated and will be removed in a future version. "
+                "Use equal_variance instead.",
+                DeprecationWarning,
+                stacklevel=2,
+            )
+            if equal_variance is None:
+                equal_variance = kwargs.pop("t_test_equal_var")
         super().__init__(
             experiment=self._make_experiment(
                 additional_tests,