ENH: test indexing with arrays

Author: ev-br

Diff for: array_api_tests/test_array_object.py

@@ -242,6 +242,57 @@ def test_setitem_masking(shape, data):
             )
 
 
+@given(shape=hh.shapes(), data=st.data())
+def test_getitem_arrays_and_ints(shape, data):
+    assume((len(shape) > 0) and all(sh > 0 for sh in shape))
+
+    dtype = xp.int64
+    obj = data.draw(scalar_objects(dtype, shape), label="obj")
+    x = xp.asarray(obj, dtype=dtype)
+
+    # draw a mix of ints and index arrays
+    arr_index = [data.draw(st.booleans()) for _ in range(len(shape))]
+    assume(sum(arr_index) > 0)
+
+    # draw shapes for index arrays
+    if sum(arr_index) > 0:
+        index_shapes = data.draw(
+            hh.mutually_broadcastable_shapes(sum(arr_index), min_dims=1, min_side=1)
+        )
+        index_shapes = list(index_shapes)
+
+    # prepare the indexing tuple, a mix of integer indices and index arrays
+    key = []
+    for i,typ in enumerate(arr_index):
+        if typ:
+            # draw an array index
+            this_idx = data.draw(
+                xps.arrays(
+                    xp.int64,
+                    shape=index_shapes.pop(),
+                    elements=st.integers(0, shape[i]-1)
+                )
+            )
+            key.append(this_idx)
+
+        else:
+            # draw an integer
+            key.append(data.draw(st.integers(-shape[i], shape[i]-1)))
+
+    key = tuple(key)
+    out = x[key]
+
+    # XXX: how to properly check
+    import numpy as np
+    x_np = np.asarray(x)
+    out_np = np.asarray(out)
+    key_np = tuple(k if isinstance(k, int) else np.asarray(k) for k in key)
+
+    print(f"{x.shape = } {out.shape} -- {[k if isinstance(k, int) else k.shape for k in key]}")
+
+    np.testing.assert_equal(out_np, x_np[key_np])
+
+
 def make_scalar_casting_param(
     method_name: str, dtype: DataType, stype: ScalarType
 ) -> Param: