#2 Cosmetic and style updates

stree/Strees.py

@@ -268,7 +268,8 @@ class Splitter:
             data = self.decision_criteria(data, node._y)
         self._down = data > 0
 
-    def _distances(self, node: Snode, data: np.ndarray) -> np.array:
+    @staticmethod
+    def _distances(node: Snode, data: np.ndarray) -> np.array:
         """Compute distances of the samples to the hyperplane of the node
 
         :param node: node containing the svm classifier
@@ -498,7 +499,8 @@ class Stree(BaseEstimator, ClassifierMixin):
             )
         )
 
-    def _reorder_results(self, y: np.array, indices: np.array) -> np.array:
+    @staticmethod
+    def _reorder_results(y: np.array, indices: np.array) -> np.array:
         """Reorder an array based on the array of indices passed
 
         :param y: data untidy
@@ -579,7 +581,7 @@ class Stree(BaseEstimator, ClassifierMixin):
         X, y = check_X_y(X, y)
         y_pred = self.predict(X).reshape(y.shape)
         # Compute accuracy for each possible representation
-        y_type, y_true, y_pred = _check_targets(y, y_pred)
+        _, y_true, y_pred = _check_targets(y, y_pred)
         check_consistent_length(y_true, y_pred, sample_weight)
         score = y_true == y_pred
         return _weighted_sum(score, sample_weight, normalize=True)

stree/tests/Splitter_test.py

@@ -13,8 +13,8 @@ class Splitter_test(unittest.TestCase):
         self._random_state = 1
         super().__init__(*args, **kwargs)
 
+    @staticmethod
     def build(
-        self,
         clf=LinearSVC(),
         min_samples_split=0,
         splitter_type="random",

stree/tests/Stree_test.py

@@ -67,9 +67,8 @@ class Stree_test(unittest.TestCase):
             clf.fit(*load_dataset(self._random_state))
             self._check_tree(clf.tree_)
 
-    def _find_out(
-        self, px: np.array, x_original: np.array, y_original
-    ) -> list:
+    @staticmethod
+    def _find_out(px: np.array, x_original: np.array, y_original) -> list:
         """Find the original values of y for a given array of samples
 
         Arguments:
@@ -163,7 +162,8 @@ class Stree_test(unittest.TestCase):
         self.assertListEqual(expected, computed)
         self.assertEqual(expected_string, str(clf))
 
-    def test_is_a_sklearn_classifier(self):
+    @staticmethod
+    def test_is_a_sklearn_classifier():
         import warnings
         from sklearn.exceptions import ConvergenceWarning