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
- keepdims : [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
# Python Program illustrating# numpy.amax() methodimport numpy as geek# 1D arrayarr = geek.arange(8)print("arr : ", arr)print("Max of arr : ", geek.amax(arr))# 2D arrayarr = geek.arange(10).reshape(2, 5)print("\narr : ", arr)# Maximum of the flattened arrayprint("\nMax of arr, axis = None : ", geek.amax(arr))# Maxima along the first axis# axis 0 means verticalprint("Max of arr, axis = 0 : ", geek.amax(arr, axis = 0))# Maxima along the second axis# axis 1 means horizontalprint("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 IDE’s. So please, run them on your systems to explore the working.
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