Merge pull request #19378 from henryiii/patch-1

DOC: fix remaining np.min/np.max usages

1 files changed, 8 insertions, 8 deletions

diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py
index 820d6831f..ee93da901 100644
--- a/numpy/core/fromnumeric.py
+++ b/numpy/core/fromnumeric.py
@@ -1183,11 +1183,11 @@ def argmax(a, axis=None, out=None):
 
     >>> x = np.array([[4,2,3], [1,0,3]])
     >>> index_array = np.argmax(x, axis=-1)
-    >>> # Same as np.max(x, axis=-1, keepdims=True)
+    >>> # Same as np.amax(x, axis=-1, keepdims=True)
     >>> np.take_along_axis(x, np.expand_dims(index_array, axis=-1), axis=-1)
     array([[4],
            [3]])
-    >>> # Same as np.max(x, axis=-1)
+    >>> # Same as np.amax(x, axis=-1)
     >>> np.take_along_axis(x, np.expand_dims(index_array, axis=-1), axis=-1).squeeze(axis=-1)
     array([4, 3])
 
@@ -1264,11 +1264,11 @@ def argmin(a, axis=None, out=None):
 
     >>> x = np.array([[4,2,3], [1,0,3]])
     >>> index_array = np.argmin(x, axis=-1)
-    >>> # Same as np.min(x, axis=-1, keepdims=True)
+    >>> # Same as np.amin(x, axis=-1, keepdims=True)
     >>> np.take_along_axis(x, np.expand_dims(index_array, axis=-1), axis=-1)
     array([[2],
            [0]])
-    >>> # Same as np.max(x, axis=-1)
+    >>> # Same as np.amax(x, axis=-1)
     >>> np.take_along_axis(x, np.expand_dims(index_array, axis=-1), axis=-1).squeeze(axis=-1)
     array([2, 0])
 
@@ -2740,14 +2740,14 @@ def amax(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue,
     You can use an initial value to compute the maximum of an empty slice, or
     to initialize it to a different value:
 
-    >>> np.max([[-50], [10]], axis=-1, initial=0)
+    >>> np.amax([[-50], [10]], axis=-1, initial=0)
     array([ 0, 10])
 
     Notice that the initial value is used as one of the elements for which the
     maximum is determined, unlike for the default argument Python's max
     function, which is only used for empty iterables.
 
-    >>> np.max([5], initial=6)
+    >>> np.amax([5], initial=6)
     6
     >>> max([5], default=6)
     5
@@ -2863,7 +2863,7 @@ def amin(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue,
     >>> np.nanmin(b)
     0.0
 
-    >>> np.min([[-50], [10]], axis=-1, initial=0)
+    >>> np.amin([[-50], [10]], axis=-1, initial=0)
     array([-50,   0])
 
     Notice that the initial value is used as one of the elements for which the
@@ -2872,7 +2872,7 @@ def amin(a, axis=None, out=None, keepdims=np._NoValue, initial=np._NoValue,
 
     Notice that this isn't the same as Python's ``default`` argument.
 
-    >>> np.min([6], initial=5)
+    >>> np.amin([6], initial=5)
     5
     >>> min([6], default=5)
     6