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authorMark Wiebe <mwwiebe@gmail.com>2011-04-13 14:44:42 -0700
committerMark Wiebe <mwwiebe@gmail.com>2011-04-22 14:04:33 -0700
commitd97a5e37b2085db9558ff64716e29e6cbf791a4c (patch)
tree15ea69879054a69a7f701454500860b34d9e24b1 /doc/source/reference/ufuncs.rst
parent973b112dfde7e1263914b5b8891b9833af80441b (diff)
downloadnumpy-d97a5e37b2085db9558ff64716e29e6cbf791a4c.tar.gz
DOC: Improve the documentation about type promotion
Diffstat (limited to 'doc/source/reference/ufuncs.rst')
-rw-r--r--doc/source/reference/ufuncs.rst12
1 files changed, 9 insertions, 3 deletions
diff --git a/doc/source/reference/ufuncs.rst b/doc/source/reference/ufuncs.rst
index dedbf2929..987a2ec15 100644
--- a/doc/source/reference/ufuncs.rst
+++ b/doc/source/reference/ufuncs.rst
@@ -174,6 +174,13 @@ Casting Rules
.. index::
pair: ufunc; casting rules
+.. note::
+
+ In NumPy 1.6.0, a type promotion API was created to encapsulate the
+ mechansim for determining output types. See the functions
+ :func:`result_type`, :func:`promote_types`, and
+ :func:`min_scalar_type` for more details.
+
At the core of every ufunc is a one-dimensional strided loop that
implements the actual function for a specific type combination. When a
ufunc is created, it is given a static list of inner loops and a
@@ -267,15 +274,14 @@ types, are interpreted accordingly in ufuncs) without worrying about
whether the precision of the scalar constant will cause upcasting on
your large (small precision) array.
-
:class:`ufunc`
==============
Optional keyword arguments
--------------------------
-All ufuncs take optional keyword arguments. These represent rather
-advanced usage and will not typically be used by most Numpy users.
+All ufuncs take optional keyword arguments. Most of these represent
+advanced usage and will not typically be used.
.. index::
pair: ufunc; keyword arguments