Apply suggestions from code review

Co-authored-by: Alexander Goscinski <[email protected]>

Author: rosecers

src/skmatter/_selection.py

@@ -241,7 +241,9 @@ def transform(self, X, y=None):
             The selected subset of the input.
         """
 
-        if self.axis == 0:
+        check_is_fitted(self, ["_axis", "selected_idx_", "n_selected_"])
+
+        if self._axis == 0:
             raise ValueError(
                 "Transform is not currently supported for sample selection."
             )
@@ -251,7 +253,7 @@ def transform(self, X, y=None):
         X = check_array(X)
 
         if len(X.shape) == 1:
-            if self.axis == 0:
+            if self._axis == 0:
                 X = X.reshape(-1, 1)
             else:
                 X = X.reshape(1, -1)

tests/test_greedy_selector.py

@@ -62,7 +62,6 @@ def test_bad_warm_start(self):
     def test_bad_y(self):
         self.X, self.Y = get_dataset(return_X_y=True)
         Y = self.Y[:2]
-        print(self.X.shape, Y.shape)
         selector = GreedyTester(n_to_select=2)
         with self.assertRaises(ValueError):
             selector.fit(X=self.X, y=Y)

tests/test_orthogonalizers.py

@@ -152,12 +152,10 @@ def test_copy(self):
             -1, 1, size=(self.n_samples, self.n_features)
         )
 
-        print(X_random)
         idx = self.random_state.choice(X_random.shape[-1])
 
         new_X = X_orthogonalizer(X_random, idx, tol=EPSILON, copy=True)
         X_orthogonalizer(X_random, idx, tol=EPSILON, copy=False)
-        print(new_X, X_random)
         self.assertTrue(np.allclose(X_random, new_X))