BUF: Fix np.insert to handle boolean arrays as masks and remove FutureWarning and change the corresponding test (numpy#27615)

* Fix np.insert to correctly handle boolean arrays as masks

* Fix np.insert to correctly handle boolean arrays as masks

* Fix np.insert to correctly handle boolean arrays as masks and change the Corresponding test

Author: nocoding03

numpy/lib/_function_base_impl.py

@@ -5380,11 +5380,13 @@ def insert(arr, obj, values, axis=None):
     ----------
     arr : array_like
         Input array.
-    obj : int, slice or sequence of ints
+    obj : slice, int, array-like of ints or bools
         Object that defines the index or indices before which `values` is
         inserted.
 
-        .. versionadded:: 1.8.0
+        .. versionchanged:: 2.1.2
+            Boolean indices are now treated as a mask of elements to insert,
+            rather than being cast to the integers 0 and 1.
 
         Support for multiple insertions when `obj` is a single scalar or a
         sequence with one element (similar to calling insert multiple
@@ -5491,18 +5493,10 @@ def insert(arr, obj, values, axis=None):
         # need to copy obj, because indices will be changed in-place
         indices = np.array(obj)
         if indices.dtype == bool:
-            # See also delete
-            # 2012-10-11, NumPy 1.8
-            warnings.warn(
-                "in the future insert will treat boolean arrays and "
-                "array-likes as a boolean index instead of casting it to "
-                "integer", FutureWarning, stacklevel=2)
-            indices = indices.astype(intp)
-            # Code after warning period:
-            #if obj.ndim != 1:
-            #    raise ValueError('boolean array argument obj to insert '
-            #                     'must be one dimensional')
-            #indices = np.flatnonzero(obj)
+            if obj.ndim != 1:
+                raise ValueError('boolean array argument obj to insert '
+                                'must be one dimensional')
+            indices = np.flatnonzero(obj)
         elif indices.ndim > 1:
             raise ValueError(
                 "index array argument obj to insert must be one dimensional "

numpy/lib/tests/test_function_base.py

@@ -557,13 +557,9 @@ def test_basic(self):
         b = np.array([0, 1], dtype=np.float64)
         assert_equal(insert(b, 0, b[0]), [0., 0., 1.])
         assert_equal(insert(b, [], []), b)
-        # Bools will be treated differently in the future:
-        # assert_equal(insert(a, np.array([True]*4), 9), [9, 1, 9, 2, 9, 3, 9])
-        with warnings.catch_warnings(record=True) as w:
-            warnings.filterwarnings('always', '', FutureWarning)
-            assert_equal(
-                insert(a, np.array([True] * 4), 9), [1, 9, 9, 9, 9, 2, 3])
-            assert_(w[0].category is FutureWarning)
+        assert_equal(insert(a, np.array([True]*4), 9), [9, 1, 9, 2, 9, 3, 9])
+        assert_equal(insert(a, np.array([True, False, True, False]), 9),
+                     [9, 1, 2, 9, 3])
 
     def test_multidim(self):
         a = [[1, 1, 1]]