UPD: change name of alpha method

mapie/regression/time_series_regression.py

@@ -167,7 +167,7 @@ def partial_fit(
         ] = new_conformity_scores_
         return self
 
-    def init_alpha(
+    def _get_alpha(
         self,
         alpha: Optional[Union[float, Iterable[float]]] = None,
         reset: bool = False
@@ -251,7 +251,7 @@ def adapt_conformal_inference(
         X, y = cast(NDArray, X), cast(NDArray, y)
         X, y = convert_to_numpy(X, y)
 
-        self.init_alpha()
+        self._get_alpha()
         alpha = cast(Optional[NDArray], check_alpha(alpha))
         if alpha is None:
             alpha = np.array(list(self.current_alpha.keys()))
@@ -387,7 +387,7 @@ def predict(
             super().predict(X, ensemble, alpha, optimize_beta)
 
         if self.method == "aci":
-            alpha = self.init_alpha(alpha)
+            alpha = self._get_alpha(alpha)
 
         return super().predict(X, ensemble, alpha, optimize_beta)
 

mapie/tests/test_time_series_regression.py

@@ -477,17 +477,17 @@ def test_aci_method() -> None:
 
 
 def test_aci_init_and_reset_alpha_dict() -> None:
-    """Test that `init_alpha` resets all the values in the dictionary."""
+    """Test that `_get_alpha` resets all the values in the dictionary."""
     mapie_ts_reg = MapieTimeSeriesRegressor(method="aci")
-    mapie_ts_reg.init_alpha()
+    mapie_ts_reg._get_alpha()
     np.testing.assert_equal(isinstance(mapie_ts_reg.current_alpha, dict), True)
 
     mapie_ts_reg.current_alpha[0.05] = 0.45
-    mapie_ts_reg.init_alpha(reset=True)
+    mapie_ts_reg._get_alpha(reset=True)
     np.testing.assert_equal(bool(mapie_ts_reg.current_alpha), False)
 
 
-def test_aci_init_alpha_with_unknown_alpha() -> None:
+def test_aci__get_alpha_with_unknown_alpha() -> None:
     """
     Test that the `adapt_conformal_inference` method initializes
     a new value if alpha is seen for the first time.