numpy.amax() in Python

numpy.amax(arr, axis = None, out = None, keepdims = <class numpy._globals._NoValue>) returns maximum of an array or maximum along axis(if mentioned).

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 –

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# 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))   

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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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