diff options
author | Julian Taylor <jtaylor.debian@googlemail.com> | 2014-03-04 01:08:12 +0100 |
---|---|---|
committer | Julian Taylor <jtaylor.debian@googlemail.com> | 2014-03-04 18:35:49 +0100 |
commit | f6800f561ae3d148a4948512caa5ae23f5f27f78 (patch) | |
tree | ca0ee001c6ca6f65c6ef66b6803a1995ea2c2fe0 /numpy/lib/shape_base.py | |
parent | d4c7c3a69a0dc2458c876dd17a15b1a18b179fd8 (diff) | |
download | numpy-f6800f561ae3d148a4948512caa5ae23f5f27f78.tar.gz |
DOC: document equivalence of apply_over_axes and tuple axis ufuncs
Diffstat (limited to 'numpy/lib/shape_base.py')
-rw-r--r-- | numpy/lib/shape_base.py | 13 |
1 files changed, 13 insertions, 0 deletions
diff --git a/numpy/lib/shape_base.py b/numpy/lib/shape_base.py index c299c1976..38b928d57 100644 --- a/numpy/lib/shape_base.py +++ b/numpy/lib/shape_base.py @@ -153,6 +153,12 @@ def apply_over_axes(func, a, axes): apply_along_axis : Apply a function to 1-D slices of an array along the given axis. + Notes + ------ + This function is equivalent to tuple axis arguments to reorderable ufuncs + with keepdims=True. Tuple axis arguments to ufuncs have been availabe since + version 1.7.0. + Examples -------- >>> a = np.arange(24).reshape(2,3,4) @@ -172,6 +178,13 @@ def apply_over_axes(func, a, axes): [ 92], [124]]]) + Tuple axis arguments to ufuncs are equivalent: + + >>> np.sum(a, axis=(0,2), keepdims=True) + array([[[ 60], + [ 92], + [124]]]) + """ val = asarray(a) N = a.ndim |