The numpy.argmax() function returns indices of the max element of the array in a particular axis.
Syntax :
numpy.argmax(array, axis = None, out = None)
Parameters :
array : Input array to work on
axis : [int, optional]Along a specified axis like 0 or 1
out : [array optional]Provides a feature to insert output to the out
array and it should be of appropriate shape and dtype
Return :
Array of indices into the array with same shape as array.shape
with the dimension along axis removed.
Code 1 :
Python
import numpy as geek
array = geek.arange( 12 ).reshape( 3 , 4 )
print ( "INPUT ARRAY : \n" , array)
print ( "\nMax element : " , geek.argmax(array))
print ( "\nIndices of Max element : " , geek.argmax(array, axis = 0 ))
print ( "\nIndices of Max element : " , geek.argmax(array, axis = 1 ))
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Output :
INPUT ARRAY :
[[ 0 1 2 3]
[ 4 5 6 7]
[ 8 9 10 11]]
Max element : 11
Indices of Max element : [2 2 2 2]
Indices of Max element : [3 3 3]
Code 2 :
Python
import numpy as geek
array = geek.random.randint( 16 , size = ( 4 , 4 ))
print ( "INPUT ARRAY : \n" , array)
print ( "\nMax element : " , geek.argmax(array))
print ( "\nIndices of Max element : " , geek.argmax(array, axis = 0 ))
print ( "\nIndices of Max element : " , geek.argmax(array, axis = 1 ))
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Output :
INPUT ARRAY :
[[ 0 3 8 13]
[12 11 2 11]
[ 5 13 8 3]
[12 15 3 4]]
Max element : 15
Indices of Max element : [1 3 0 0]
Indices of Max element : [3 0 1 1]
Code 3 :
Python
import numpy as geek
array = geek.arange( 10 ).reshape( 2 , 5 )
print ( "array : \n" , array)
array[ 0 ][ 1 ] = 6
print ( "\narray : \n" , array)
print ( "\narray : " , geek.argmax(array))
print ( "\nMAX ELEMENT INDICES : " , geek.argmax(array, axis = 0 ))
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Output :
array :
[[0 1 2 3 4]
[5 6 7 8 9]]
array :
[[0 6 2 3 4]
[5 6 7 8 9]]
array : 9
MAX ELEMENT INDICES : [1 0 1 1 1]
Note :
These codes won’t run on online IDE’s. Please run them on your systems to explore the working.
Last Updated :
08 Mar, 2024
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