BUG: automatically convert recarray dtype to np.record

Viewing an ndarray as a np.recarray now automatically converts
the dtype to np.record.

This commit also fixes assignment to MaskedArray's dtype attribute,
fixes the repr of recarrays with non-structured dtype, and removes
recarray.view so that viewing a recarray as a non-structured dtype
no longer converts to ndarray type.

Fixes #3581

1 files changed, 10 insertions, 8 deletions

diff --git a/doc/source/reference/arrays.dtypes.rst b/doc/source/reference/arrays.dtypes.rst
index 28e2d4f82..8f14118d6 100644
--- a/doc/source/reference/arrays.dtypes.rst
+++ b/doc/source/reference/arrays.dtypes.rst
@@ -424,16 +424,18 @@ Type strings
 
 ``(base_dtype, new_dtype)``
 
-    This usage is discouraged. In NumPy 1.7 and later, it is possible
-    to specify struct dtypes with overlapping fields, functioning like
-    the 'union' type in C. The union mechanism is preferred.
-
-    Both arguments must be convertible to data-type objects in this
-    case. The *base_dtype* is the data-type object that the new
-    data-type builds on. This is how you could assign named fields to
-    any built-in data-type object, as done in
+    In NumPy 1.7 and later, this form allows `base_dtype` to be interpreted as
+    a structured dtype. Arrays created with this dtype will have underlying
+    dtype `base_dtype` but will have fields and flags taken from `new_dtype`.
+    This is useful for creating custom structured dtypes, as done in
     :ref:`record arrays <arrays.classes.rec>`.
 
+    This form also makes it possible to specify struct dtypes with overlapping
+    fields, functioning like the 'union' type in C. This usage is discouraged,
+    however, and the union mechanism is preferred.
+
+    Both arguments must be convertible to data-type objects with the same total
+    size.
     .. admonition:: Example
 
        32-bit integer, whose first two bytes are interpreted as an integer