Correct doc and Readme.rst and Fix typing errors

Author: adriencrtrcap

docs/analysis.rst

@@ -45,7 +45,7 @@ The MCAR missing-data mechanism means that there is independence between the pre
 a. Little's Test
 ^^^^^^^^^^^^^^^^
 
-The best-known MCAR test is the :ref:`Little [2]<Little-article>` test, and it has been implemented in :class:`LittleTest`. Keep in mind that the Little's test is designed to test the homogeneity of means across the missing patterns and won't be efficient to detect the heterogeneity of covariance accross missing patterns.
+The best-known MCAR test is the :ref:`Little [1]<Little-article>` test, and it has been implemented in :class:`LittleTest`. Keep in mind that the Little's test is designed to test the homogeneity of means across the missing patterns and won't be efficient to detect the heterogeneity of covariance accross missing patterns.
 
 b. PKLM Test
 ^^^^^^^^^^^^

docs/images/schema_qolmat.png

@@ -53,7 +53,7 @@ twine = "3.7.1"
 wheel = "0.37.1"
 category-encoders = "^2.6.3"
 ipykernel = "^6.29.5"
-torch = "^2.4.0"
+torch = "*"
 
 [tool.poetry.dev-dependencies]
 matplotlib = "3.6.2"

pyproject.toml

@@ -334,7 +334,7 @@ def _draw_features_and_target_indexes(
     @staticmethod
     def _check_draw(
         X: np.ndarray, features_idx: List[int], target_idx: int
-    ) -> np.bool_:
+    ) -> bool:
         """Check if the drawn features and target are valid.
 
         Here we check
@@ -365,7 +365,7 @@ def _check_draw(
 
     def _generate_label_feature_combinations(
         self, X: np.ndarray
-    ) -> List[Tuple[int, List[int]]]:
+    ) -> List[Tuple[List[int], int]]:
         """Generate all valid combinations of features and labels.
 
         Parameters
@@ -687,7 +687,7 @@ def _compute_partial_p_value(
 
         """
         U_k = B[k, :] @ U
-        p_v_k = 1
+        p_v_k = 1.
 
         for u_sigma_k in (B[k, :] @ U_sigma).tolist():
             if u_sigma_k >= U_k:
@@ -745,7 +745,7 @@ def test(
         U = U / self.nb_projections
         list_U_sigma = [x / self.nb_permutation for x in list_U_sigma]
 
-        p_value = 1
+        p_value = 1.
         for u_sigma in list_U_sigma:
             if u_sigma >= U:
                 p_value += 1