BUG: Always return views from structured_to_unstructured when possible

Also applies to unstructured_to_structured

While producing correct resutls, the test added in this commit would previously make an unecessary copy, causing the assertion to fail.
The cause was `astype` was being asked to convert from a subarray of shape `(x, y)` to one of `(x*y,)`, which it cannot do without making a copy.

This changes the approach used to skip the step of flattening subarrays to 1d

1 files changed, 2 insertions, 2 deletions

diff --git a/numpy/lib/recfunctions.py b/numpy/lib/recfunctions.py
index bf588a490..d412281ff 100644
--- a/numpy/lib/recfunctions.py
+++ b/numpy/lib/recfunctions.py
@@ -972,7 +972,7 @@ def structured_to_unstructured(arr, dtype=None, copy=False, casting='unsafe'):
 
     # next cast to a packed format with all fields converted to new dtype
     packed_fields = np.dtype({'names': names,
-                              'formats': [(out_dtype, c) for c in counts]})
+                              'formats': [(out_dtype, dt.shape) for dt in dts]})
     arr = arr.astype(packed_fields, copy=copy, casting=casting)
 
     # finally is it safe to view the packed fields as the unstructured type
@@ -1065,7 +1065,7 @@ def unstructured_to_structured(arr, dtype=None, names=None, align=False,
 
     # first view as a packed structured array of one dtype
     packed_fields = np.dtype({'names': names,
-                              'formats': [(arr.dtype, c) for c in counts]})
+                              'formats': [(arr.dtype, dt.shape) for dt in dts]})
     arr = np.ascontiguousarray(arr).view(packed_fields)
 
     # next cast to an unpacked but flattened format with varied dtypes