Merge pull request #350 from jayvius/get-view2

Add transition code for returning view when selecting subset of fields

2 files changed, 17 insertions, 0 deletions

diff --git a/doc/release/1.7.0-notes.rst b/doc/release/1.7.0-notes.rst
index e8b1de72d..f8f54219c 100644
--- a/doc/release/1.7.0-notes.rst
+++ b/doc/release/1.7.0-notes.rst
@@ -26,6 +26,13 @@ functions. To facilitate this transition, numpy 1.7 produces a
 FutureWarning if it detects that you may be attempting to write to
 such an array. See the documentation for np.diagonal for details.
 
+Similar to np.diagonal above, in a future version of numpy, indexing
+a record array by a list of field names will return a view onto the
+original array, instead of producing a copy as they do now. As with
+np.diagonal, numpy 1.7 produces a FutureWarning if it detects
+that you may be attemping to write to such an array. See the documentation
+for array indexing for details.
+
 The default casting rule for UFunc out= parameters has been changed from
 'unsafe' to 'same_kind'.  Most usages which violate the 'same_kind'
 rule are likely bugs, so this change may expose previously undetected
diff --git a/doc/source/reference/arrays.indexing.rst b/doc/source/reference/arrays.indexing.rst
index 8da4ecca7..f8966f5c1 100644
--- a/doc/source/reference/arrays.indexing.rst
+++ b/doc/source/reference/arrays.indexing.rst
@@ -335,6 +335,16 @@ sub-array) but of data type ``x.dtype['field-name']`` and contains
 only the part of the data in the specified field. Also record array
 scalars can be "indexed" this way.
 
+Indexing into a record array can also be done with a list of field names,
+*e.g.* ``x[['field-name1','field-name2']]``. Currently this returns a new
+array containing a copy of the values in the fields specified in the list.
+As of NumPy 1.7, returning a copy is being deprecated in favor of returning
+a view. A copy will continue to be returned for now, but a FutureWarning
+will be issued when writing to the copy. If you depend on the current
+behavior, then we suggest copying the returned array explicitly, i.e. use
+x[['field-name1','field-name2']].copy(). This will work with both past and
+future versions of NumPy.
+
 If the accessed field is a sub-array, the dimensions of the sub-array
 are appended to the shape of the result.