Expand test_asarray.py.

* Improve comments/docs.
* Improve descriptiveness of variable names.
* Add additional test expressions that would not pass without
  this patch.

1 files changed, 33 insertions, 13 deletions

diff --git a/numpy/array_api/tests/test_asarray.py b/numpy/array_api/tests/test_asarray.py
index bd1859d71..fdcc77506 100644
--- a/numpy/array_api/tests/test_asarray.py
+++ b/numpy/array_api/tests/test_asarray.py
@@ -1,24 +1,44 @@
 import numpy as np
 
 
-def test_fast_return():
-    """"""
-    a = np.array([1, 2, 3], dtype='i')
-    assert np.asarray(a) is a
-    assert np.asarray(a, dtype='i') is a
-    # This may produce a new view or a copy, but is never the same object.
-    assert np.asarray(a, dtype='l') is not a
+def test_dtype_identity():
+    """Confirm the intended behavior for ``asarray`` results.
 
+    The result of ``asarray()`` should have the dtype provided through the
+    keyword argument, when used. This forces unique array handles to be
+    produced for unique np.dtype objects, but (for equivalent dtypes), the
+    underlying data (the base object) is shared with the original array object.
+
+    Ref https://github.com/numpy/numpy/issues/1468
+    """
+    int_array = np.array([1, 2, 3], dtype='i')
+    assert np.asarray(int_array) is int_array
+
+    # The character code resolves to the singleton dtype object provided
+    # by the numpy package.
+    assert np.asarray(int_array, dtype='i') is int_array
+
+    # Derive a dtype from n.dtype('i'), but add a metadata object to force
+    # the dtype to be distinct.
     unequal_type = np.dtype('i', metadata={'spam': True})
-    b = np.asarray(a, dtype=unequal_type)
-    assert b is not a
-    assert b.base is a
+    annotated_int_array = np.asarray(int_array, dtype=unequal_type)
+    assert annotated_int_array is not int_array
+    assert annotated_int_array.base is int_array
+
+    # These ``asarray()`` calls may produce a new view or a copy,
+    # but never the same object.
+    long_int_array = np.asarray(int_array, dtype='l')
+    assert long_int_array is not int_array
+    assert np.asarray(int_array, dtype='q') is not int_array
+    assert np.asarray(long_int_array, dtype='q') is not long_int_array
+    assert np.asarray(int_array, dtype='l') is not np.asarray(int_array, dtype='l')
+    assert np.asarray(int_array, dtype='l').base is np.asarray(int_array, dtype='l').base
 
     equivalent_requirement = np.dtype('i', metadata={'spam': True})
-    c = np.asarray(b, dtype=equivalent_requirement)
+    annotated_int_array_alt = np.asarray(annotated_int_array, dtype=equivalent_requirement)
     # The descriptors are equivalent, but we have created
     # distinct dtype instances.
     assert unequal_type == equivalent_requirement
     assert unequal_type is not equivalent_requirement
-    assert c is not b
-    assert c.dtype is equivalent_requirement
+    assert annotated_int_array_alt is not annotated_int_array
+    assert annotated_int_array_alt.dtype is equivalent_requirement