Add scalar support to where

cubed/array_api/searching_functions.py

@@ -88,5 +88,13 @@ def _searchsorted(x, y, side):
 
 
 def where(condition, x1, x2, /):
+    x1_is_scalar = isinstance(x1, (int, float, complex, bool))
+    x2_is_scalar = isinstance(x2, (int, float, complex, bool))
+    if x1_is_scalar and x2_is_scalar:
+        raise TypeError("At least one of x1 and x2 must be an array in where")
+    elif x1_is_scalar:
+        x1 = x2._promote_scalar(x1)
+    elif x2_is_scalar:
+        x2 = x1._promote_scalar(x2)
     dtype = result_type(x1, x2)
     return elemwise(nxp.where, condition, x1, x2, dtype=dtype)

cubed/tests/test_array_api.py

@@ -794,6 +794,22 @@ def test_searchsorted_sorter_not_implemented():
         xp.searchsorted(xp.asarray([1, 0]), xp.asarray([1]), sorter=xp.asarray([1, 0]))
 
 
+def test_where_scalars():
+    condition = xp.asarray(
+        [[True, False, True], [False, True, False], [True, False, True]], chunks=(2, 2)
+    )
+    a = xp.asarray([[1, 2, 3], [4, 5, 6], [7, 8, 9]], chunks=(2, 2))
+
+    b = xp.where(condition, a, 0)
+    assert_array_equal(b.compute(), np.array([[1, 0, 3], [0, 5, 0], [7, 0, 9]]))
+
+    c = xp.where(condition, 0, a)
+    assert_array_equal(c.compute(), np.array([[0, 2, 0], [4, 0, 6], [0, 8, 0]]))
+
+    with pytest.raises(TypeError):
+        xp.where(condition, 0, 1)
+
+
 # Statistical functions