numpy.argmin (array, axis = None, out = None): returns the indices of the minimum element in an array on a specific axis.
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 :
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import numpy as geek
a rray = geek.arange ( 8 )
print ( "INPUT ARRAY:" , array)
print ( "Indices of min element: " , geek.argmin (array, axis = 0 ))
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Output:
INPUT ARRAY: [0 1 2 3 4 5 6 7] Indices of min element: 0
Code 2:
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import numpy as geek
array = geek.random.randint ( 16 , size = ( 4 , 4 ))
print ( "INPUT ARRAY:" , array)
print ( "Indices of min element: " , geek.argmin (array, axis = 0 ))
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Output:
INPUT ARRAY: [[8 13 5 0] [0 2 5 3] [10 7 15 15] [3 11 4 12]] Indices of min element: [1 1 3 0]
Code 3:
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import numpy as geek
array = geek.arange ( 10 ). Reshape ( 2 , 5 )
print ( "array:" , array)
array [ 0 ] [ 0 ] = 10
array [ 1 ] [ 1 ] = 1
array [ 0 ] [ 1 ] = 1
print ( "array: " , array)
print ( "array:" , geek.argmin (array))
print ( "min ELEMENT INDICES:" , geek.argmin (array, axis = 0 ))
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Output:
array: [[0 1 2 3 4] [5 6 7 8 9]] array: [[10 1 2 3 4] [5 1 7 8 9]] array: 1 min ELEMENT INDICES: [1 0 0 0 0]
Links:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.argmin.html#numpy.argmin
Notes:
These codes will not work for online IDs. Please run them on your systems to see how they work
This article is provided by Mohit Gupta_OMG
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