Merge pull request #7015 from njsmith/fix-1.10-messages

charris · charris · commit a97f3a672637 · 2016-01-14T18:30:58.000-07:00
DOC: Clean up/fix several references to the "future" 1.10 release
diff --git a/doc/source/reference/ufuncs.rst b/doc/source/reference/ufuncs.rst
@@ -333,8 +333,8 @@ advanced usage and will not typically be used.
     with previous versions of NumPy, this defaults to 'unsafe' for numpy < 1.7.
     In numpy 1.7 a transition to 'same_kind' was begun where ufuncs produce a
     DeprecationWarning for calls which are allowed under the 'unsafe'
-    rules, but not under the 'same_kind' rules. In numpy 1.10 the default
-    will be 'same_kind'.
+    rules, but not under the 'same_kind' rules. From numpy 1.10 and
+    onwards, the default is 'same_kind'.
 
 *order*
 
diff --git a/numpy/add_newdocs.py b/numpy/add_newdocs.py
@@ -3466,7 +3466,7 @@ def luf(lamdaexpr, *args, **kwargs):
 
     Return specified diagonals. In NumPy 1.9 the returned array is a
     read-only view instead of a copy as in previous NumPy versions.  In
-    NumPy 1.10 the read-only restriction will be removed.
+    a future version the read-only restriction will be removed.
 
     Refer to :func:`numpy.diagonal` for full documentation.
 
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
@@ -1217,11 +1217,11 @@ def diagonal(a, offset=0, axis1=0, axis2=1):
     but depending on this fact is deprecated. Writing to the resulting
     array continues to work as it used to, but a FutureWarning is issued.
 
-    In NumPy 1.9 it returns a read-only view on the original array.
+    Starting in NumPy 1.9 it returns a read-only view on the original array.
     Attempting to write to the resulting array will produce an error.
 
-    In NumPy 1.10, it will return a read/write view and writing to the
-    returned array will alter your original array.  The returned array
+    In some future release, it will return a read/write view and writing to
+    the returned array will alter your original array.  The returned array
     will have the same type as the input array.
 
     If you don't write to the array returned by this function, then you can
