TST: Move new `asarray` test to a more appropriate place. (#22251)

As noted at #21995 (comment), the new test from #21995 was placed in a directory intended for the Array API, and unrelated to the change.

* Consolidate test_dtype_identity into an existing test file.

Remove `test_asarray.py`. Create a new `TestAsArray` suite in
`test_array_coercion.py`

* Linting.

Wrap some comments that got too long after function became
a method (with additional indentation).

1 files changed, 0 insertions, 64 deletions

diff --git a/numpy/array_api/tests/test_asarray.py b/numpy/array_api/tests/test_asarray.py
deleted file mode 100644
index 5c269823f..000000000
--- a/numpy/array_api/tests/test_asarray.py
+++ /dev/null
@@ -1,64 +0,0 @@
-import itertools
-
-import numpy as np
-
-
-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})
-    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
-    # Create an equivalent descriptor with a new and distinct dtype instance.
-    equivalent_requirement = np.dtype('i', metadata={'spam': True})
-    annotated_int_array_alt = np.asarray(annotated_int_array,
-                                         dtype=equivalent_requirement)
-    assert unequal_type == equivalent_requirement
-    assert unequal_type is not equivalent_requirement
-    assert annotated_int_array_alt is not annotated_int_array
-    assert annotated_int_array_alt.dtype is equivalent_requirement
-
-    # Check the same logic for a pair of C types whose equivalence may vary
-    # between computing environments.
-    # Find an equivalent pair.
-    integer_type_codes = ('i', 'l', 'q')
-    integer_dtypes = [np.dtype(code) for code in integer_type_codes]
-    typeA = None
-    typeB = None
-    for typeA, typeB in itertools.permutations(integer_dtypes, r=2):
-        if typeA == typeB:
-            assert typeA is not typeB
-            break
-    assert isinstance(typeA, np.dtype) and isinstance(typeB, np.dtype)
-
-    # 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')
-    long_long_int_array = np.asarray(int_array, dtype='q')
-    assert long_int_array is not int_array
-    assert long_long_int_array is not int_array
-    assert np.asarray(long_int_array, dtype='q') is not long_int_array
-    array_a = np.asarray(int_array, dtype=typeA)
-    assert typeA == typeB
-    assert typeA is not typeB
-    assert array_a.dtype is typeA
-    assert array_a is not np.asarray(array_a, dtype=typeB)
-    assert np.asarray(array_a, dtype=typeB).dtype is typeB
-    assert array_a is np.asarray(array_a, dtype=typeB).base