DEP,BUG: Coercion/cast of array to a subarray dtype will be fixed

This currently appends the subarray dtype dimensions first and then
tries to assign to the result array which uses incorrect broadcasting
(broadcasting against the subarray dimensions instead of repeating
each element according to the subarray dimensions).

This also fixes the python scalar pathway `np.array(2, dtype="(2)f4,")`
which previously only filled the first value.  I consider that a clear
bug fix.

Closes gh-17511

2 files changed, 30 insertions, 24 deletions

diff --git a/doc/release/upcoming_changes/17419.deprecation.rst b/doc/release/upcoming_changes/17419.deprecation.rst
deleted file mode 100644
index fcab3a8ad..000000000
--- a/doc/release/upcoming_changes/17419.deprecation.rst
+++ /dev/null
@@ -1,24 +0,0 @@
-Arrays cannot be using subarray dtypes
---------------------------------------
-Array creation and casting using ``np.array(obj, dtype)``
-and ``arr.astype(dtype)`` will not support ``dtype``
-to be a subarray dtype such as ``np.dtype("(2)i,")``.
-
-For such a ``dtype`` the following behaviour occurs currently::
-
-    res = np.array(obj, dtype)
-
-    res.dtype is not dtype
-    res.dtype is dtype.base
-    res.shape[-dtype.ndim:] == dtype.shape
-
-The shape of the dtype is included into the array.
-This leads to inconsistencies when ``obj`` is:
-
-* a scalar, such as ``np.array(1, dtype="(2)i")``
-* an array, such as ``np.array(np.array([1]), dtype="(2)i")``
-
-In most cases the work-around is to pass the output dtype directly
-and possibly check ``res.shape[-dtype.ndim:] == dtype.shape``.
-If this is insufficient, please open an issue on the NumPy issue
-tracker.
diff --git a/doc/release/upcoming_changes/17596.future.rst b/doc/release/upcoming_changes/17596.future.rst
new file mode 100644
index 000000000..6e697c8d1
--- /dev/null
+++ b/doc/release/upcoming_changes/17596.future.rst
@@ -0,0 +1,30 @@
+Arrays cannot be using subarray dtypes
+--------------------------------------
+Array creation and casting using ``np.array(arr, dtype)``
+and ``arr.astype(dtype)`` will use different logic when ``dtype``
+is a subarray dtype such as ``np.dtype("(2)i,")``.
+
+For such a ``dtype`` the following behaviour is true::
+
+    res = np.array(arr, dtype)
+
+    res.dtype is not dtype
+    res.dtype is dtype.base
+    res.shape == arr.shape + dtype.shape
+
+But ``res`` is filled using the logic:
+
+    res = np.empty(arr.shape + dtype.shape, dtype=dtype.base)
+    res[...] = arr
+
+which uses incorrect broadcasting (and often leads to an error).
+In the future, this will instead cast each element individually,
+leading to the same result as::
+
+    res = np.array(arr, dtype=np.dtype(["f", dtype]))["f"]
+
+Which can normally be used to opt-in to the new behaviour.
+
+This change does not affect ``np.array(list, dtype="(2)i,")`` unless the
+``list`` itself includes at least one array.  In particular, the behaviour
+is unchanged for a list of tuples.