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| author | David Cournapeau <cournape@gmail.com> | 2009-03-09 20:31:48 +0000 |
|---|---|---|
| committer | David Cournapeau <cournape@gmail.com> | 2009-03-09 20:31:48 +0000 |
| commit | b51762ef676ac8b0c2d6e0a4d75da988572c2383 (patch) | |
| tree | a14b3519ebbd3f2fce3421a8666cba508b07552e /numpy/core/fromnumeric.py | |
| parent | 7d75121a4d11bd31ec322523da9283790ac30f75 (diff) | |
| download | numpy-b51762ef676ac8b0c2d6e0a4d75da988572c2383.tar.gz | |
Fix docstring for amax/amin.
Diffstat (limited to 'numpy/core/fromnumeric.py')
| -rw-r--r-- | numpy/core/fromnumeric.py | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index cd9762d3c..2dfabd80e 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -1519,8 +1519,8 @@ def amax(a, axis=None, out=None): >>> np.amax(a, axis=1) array([1, 3]) - Note - ---- + Notes + ----- NaN values are propagated, that is if at least one item is nan, the corresponding max value will be nan as well. To ignore NaN values (matlab behavior), please use nanmax. @@ -1571,8 +1571,8 @@ def amin(a, axis=None, out=None): >>> np.amin(a, axis=1) # Minima along the second axis array([0, 2]) - Note - ---- + Notes + ----- NaN values are propagated, that is if at least one item is nan, the corresponding min value will be nan as well. To ignore NaN values (matlab behavior), please use nanmin. |