numpy.amax() in Python

Last Updated : 17 Nov, 2020

The numpy.amax() method returns the maximum of an array or maximum along the axis(if mentioned).

Syntax:

numpy.amax(arr, axis = None, out = None, keepdims = <class numpy._globals._NoValue>)

Parameters –

arr : [array_like] input data
axis : [int or tuples of int] axis along which we want the max value. Otherwise, it will consider arr to be flattened.
out : [ndarray, optional] alternative output array in which to place the result
keepdmis : [boolean, optional] if this is set to True, the axes which are reduced are left in
the result as dimensions with size one. With this option, the result will broadcast correctly against
the input array. If the default value is passed, then keepdims will not be passed through to the all
method of sub-classes of ndarray, however any non-default value will be. If the sub-classes sum method
does not implement keepdims any exceptions will be raised.

Return – Maximum of array – arr[ndarray or scalar], scalar if axis is None; the result is an array of dimension a.ndim – 1, if axis is mentioned.

Code –

# Python Program illustrating 
# numpy.amax() method 
  
import numpy as geek 
  
# 1D array 
arr = geek.arange(8) 
print("arr : ", arr) 
print("Max of arr : ", geek.amax(arr)) 
  
# 2D array 
arr = geek.arange(10).reshape(2, 5) 
print("\narr : ", arr) 
  
# Maximum of the flattened array 
print("\nMax of arr, axis = None : ", geek.amax(arr)) 
  
# Maxima along the first axis 
# axis 0 means vertical 
print("Max of arr, axis = 0 : ", geek.amax(arr, axis = 0)) 
  
# Maxima along the second axis 
# axis 1 means horizontal 
print("Max of arr, axis = 1 : ", geek.amax(arr, axis = 1))    

Output –

arr :  [0 1 2 3 4 5 6 7]
Max of arr :  7

arr :  [[0 1 2 3 4]
 [5 6 7 8 9]]

Max of arr, axis = None :  9
Max of arr, axis = 0 :  [5 6 7 8 9]
Max of arr, axis = 1 :  [4 9]

Reference –
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.amax.html

Note –
These codes won’t run on online-ID. Please run them on your systems to explore the working

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