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authorDavid Cournapeau <cournape@gmail.com>2009-03-06 14:36:33 +0000
committerDavid Cournapeau <cournape@gmail.com>2009-03-06 14:36:33 +0000
commit9064d4b2a46fc8b725314e5fae191b8497fef5f6 (patch)
treedcb49f8af251e5dbaf9cb102b6951b320cfc4a89 /numpy/core/fromnumeric.py
parent173384a6fbe3a782f52ef30a8ffdc0a315a58880 (diff)
downloadnumpy-9064d4b2a46fc8b725314e5fae191b8497fef5f6.tar.gz
Add documentation for amin/amax.
Diffstat (limited to 'numpy/core/fromnumeric.py')
-rw-r--r--numpy/core/fromnumeric.py21
1 files changed, 21 insertions, 0 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 0023c99f0..ed66a1ccf 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -1520,6 +1520,17 @@ def amax(a, axis=None, out=None):
>>> np.amax(a, axis=1)
array([1, 3])
+ Note
+ ----
+ 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.
+
+ See Also
+ --------
+ nanmax: nan values are ignored instead of being propagated
+ fmax: same behavior as the C99 fmax function
+
"""
try:
amax = a.max
@@ -1561,6 +1572,16 @@ def amin(a, axis=None, out=None):
>>> np.amin(a, axis=1) # Minima along the second axis
array([0, 2])
+ Note
+ ----
+ 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.
+
+ See Also
+ --------
+ nanmin: nan values are ignored instead of being propagated
+ fmin: same behavior as the C99 fmin function
"""
try:
amin = a.min