Removed unnecessary test and fixed initialize

src/skmatter/_selection.py

@@ -934,7 +934,7 @@ class _FPS(GreedySelector):
     Parameters
     ----------
 
-    initialize: int, list of int, ndarray of int, or 'random', default=0
+    initialize: int, list of int, numpy.ndarray of int, or 'random', default=0
         Index of the first selection(s). If 'random', picks a random
         value when fit starts. Stored in :py:attr:`self.initialize`.
 
@@ -1038,14 +1038,7 @@ def _init_greedy_search(self, X, y, n_to_select):
         self.hausdorff_ = np.full(X.shape[self._axis], np.inf)
         self.hausdorff_at_select_ = np.full(X.shape[self._axis], np.inf)
 
-        if isinstance(self.initialize, np.ndarray):
-            if all(isinstance(i, numbers.Integral) for i in self.initialize):
-                for i, val in enumerate(self.initialize):
-                    self.selected_idx_[i] = val
-                    self._update_post_selection(X, y, self.selected_idx_[i])
-            else:
-                raise ValueError("Initialize parameter must contain only int")
-        elif self.initialize == "random":
+        if self.initialize == "random":
             random_state = check_random_state(self.random_state)
             initialize = random_state.randint(X.shape[self._axis])
             self.selected_idx_[0] = initialize
@@ -1060,6 +1053,12 @@ def _init_greedy_search(self, X, y, n_to_select):
             for i, val in enumerate(self.initialize):
                 self.selected_idx_[i] = val
                 self._update_post_selection(X, y, self.selected_idx_[i])
+        elif isinstance(self.initialize, np.ndarray) and all(
+            isinstance(i, numbers.Integral) for i in self.initialize
+        ):
+            for i, val in enumerate(self.initialize):
+                self.selected_idx_[i] = val
+                self._update_post_selection(X, y, self.selected_idx_[i])
 
         else:
             raise ValueError("Invalid value of the initialize parameter")

tests/test_feature_simple_fps.py

@@ -50,15 +50,6 @@ def test_initialize(self):
             for i in range(4):
                 self.assertEqual(selector.selected_idx_[i], self.idx[i])
 
-        initialize = np.array([1, 5, 3, 0.25])
-        with self.subTest(initialize=initialize):
-            with self.assertRaises(ValueError) as cm:
-                selector = FPS(n_to_select=len(self.idx) - 1, initialize=initialize)
-                selector.fit(self.X)
-            self.assertEqual(
-                str(cm.exception), "Initialize parameter must contain only int"
-            )
-
         with self.assertRaises(ValueError) as cm:
             selector = FPS(n_to_select=1, initialize="bad")
             selector.fit(self.X)