Handle boolean arrays in dpnp.insert as mask

Author: antonwolfy

dpnp/dpnp_iface_manipulation.py

@@ -2170,11 +2170,12 @@ def insert(arr, obj, values, axis=None):
     ----------
     arr : array_like
         Input array.
-    obj : {slice, int, array-like of ints}
+    obj : {slice, int, array-like of ints or bools}
         Object that defines the index or indices before which `values` is
         inserted. It supports multiple insertions when `obj` is a single
         scalar or a sequence with one element (similar to calling insert
         multiple times).
+        Boolean indices are treated as a mask of elements to insert.
     values : array_like
         Values to insert into `arr`. If the type of `values` is different
         from that of `arr`, `values` is converted to the type of `arr`.
@@ -2266,20 +2267,12 @@ def insert(arr, obj, values, axis=None):
             obj, sycl_queue=params.exec_q, usm_type=params.usm_type
         )
         if indices.dtype == dpnp.bool:
-            warnings.warn(
-                "In the future insert will treat boolean arrays and array-likes"
-                " as a boolean index instead of casting it to integers",
-                FutureWarning,
-                stacklevel=2,
-            )
-            indices = indices.astype(dpnp.intp)
-            # TODO: Code after warning period:
-            # if indices.ndim != 1:
-            #    raise ValueError(
-            #        "boolean array argument `obj` to insert must be "
-            #        "one-dimensional"
-            #    )
-            # indices = dpnp.nonzero(indices)[0]
+            if indices.ndim != 1:
+                raise ValueError(
+                    "boolean array argument obj to insert "
+                    "must be one dimensional"
+                )
+            indices = dpnp.flatnonzero(indices)
         elif indices.ndim > 1:
             raise ValueError(
                 "index array argument `obj` to insert must be one-dimensional "

dpnp/tests/test_manipulation.py

@@ -20,7 +20,6 @@
     get_float_dtypes,
     get_integer_dtypes,
     has_support_aspect64,
-    numpy_version,
 )
 from .third_party.cupy import testing
 
@@ -578,13 +577,13 @@ def test_ndarray_obj_values(self, obj, values):
         result = dpnp.insert(ia, obj, values)
         assert_equal(result, expected)
 
-    @pytest.mark.filterwarnings("ignore::FutureWarning")
+    @testing.with_requires("numpy>=2.2")
     @pytest.mark.parametrize(
         "obj",
-        [True, [False], numpy.array([True] * 4), [True, False, True, False]],
+        [[False], numpy.array([True] * 4), [True, False, True, False]],
     )
     def test_boolean_obj(self, obj):
-        if numpy_version() >= "2.2.0" and not isinstance(obj, numpy.ndarray):
+        if not isinstance(obj, numpy.ndarray):
             # numpy.insert raises exception
             # TODO: remove once NumPy resolves that
             obj = numpy.array(obj)
@@ -593,6 +592,19 @@ def test_boolean_obj(self, obj):
         ia = dpnp.array(a)
         assert_equal(dpnp.insert(ia, obj, 9), numpy.insert(a, obj, 9))
 
+    @testing.with_requires("numpy>=2.2")
+    @pytest.mark.parametrize("xp", [dpnp, numpy])
+    @pytest.mark.parametrize(
+        "obj_data",
+        [True, [[True, False], [True, False]]],
+        ids=["0d", "2d"],
+    )
+    def test_boolean_obj_error(self, xp, obj_data):
+        a = xp.array([1, 2, 3])
+        obj = xp.array(obj_data)
+        with pytest.raises(ValueError):
+            xp.insert(a, obj, 9)
+
     def test_1D_array(self):
         a = numpy.array([1, 2, 3])
         ia = dpnp.array(a)