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numpy.less () in Python

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numpy.less (x1, x2 [, out]): checks if x1 is less than x2 or not. 
Parameters :

  x1, x2:  [array_like] Input arrays. If x1.shape! = X2.shape, they must be broadcastable to a common shape  out:  [ndarray, boolean] Array of bools, or a single bool if x1 and x2 are scalars. 

Return:

 Boolean array indicating results, whether x1 is lesser than x2 or not. 

Code 1:

# Python program illustrating
# numpy.less () method

 

import numpy as geek 

  

= geek.less ([ 8. , 2. ], [ 5. , 3. ])

print ( "Not equal:" , a, "" )

  

b = geek.less ([ 2 , 2 ], [[ 1 , 3 ], [ 1 , 4 ]])

print ( " Not equal: " , b, " " )

 

a = geek.array ([ 4 , 2 ])

b = geek.array ([ 6 , 2 ])

  

print ( "Is a lesser than b:" , a & lt; b)

Output:

 Not equal: [False True] Not equal: [[False True] [False True]] Is a lesser than b: [True False]] 

Code 2:

# Python program illustrating
# numpy.less () method

 

import numpy as geek 

  
# Here we compare complex values ​​with int

a = geek.array ([ 1j , 2 ])

b = geek.array ([ 1 , 2 ])

  
# indicates that 1j is less than 1

print ( "Comparing complex with int:" , a & lt; b)

 
# indicates that 1j is less than 1

= geek.less (a, b)

print ( "Comparing complex with int .less (): " , d)

Output:

 Comparing complex with int: [True False] Comparing complex with int .less (): [True False] 

Code 3:

# Python program illustrating
# numpy.less () method

 

import numpy as geek 

  
# Here we compare Float with int values ​​

a = geek.array ([ 1.1 , 1 ])

b = geek.array ([ 1 , 2 ])

  
# indicates that 1.1 is greater than 1

print ( "Comparing float with int:" , a & lt; b)

 
# indicates that 1.1 is greater than 1

= geek.less (a, b)

print ( "Comparing float with int using .less (): " , d)

Output:

 Comparing float with int: [False True] Comparing float with int using .less (): [False True] 

Links:
https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.less.html#numpy.less

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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