numpy.logical_and () in Python



Parameters :

arr1: [array_like] Input array.
arr2: [array_like] Input array.

out: [ndarray, optional] Output array with same dimensions as Input array, placed with result.

** kwargs: allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function.

where: [array_like, optional] True value means to calculate the universal functions (ufunc) at that position, False value means to leave the value in the output alone.

Return:

 An array with Boolean results of arr1 and arr2 element- wise (of the same shape). 

Code 1: Working

# Python program explaining
# logic_and () function

import numpy as np

 
# login

arr1 = [ 1 , 3 , False , 4 ]

arr2 = [ 3 , 0 , True , False ]

 
# exit

out_arr = np.logical_and (arr1, arr2)

  

print ( " Output Array: " , out_arr)

Output:

 Output Array: [True False False False] 

Code 2: Value error if input arrays have different shapes

# Python program explaining
# logic_and ( ) function

i mport numpy as np

 
#input

arr1 = [ 8 , 2 , False , 4 ]

arr2 = [ 3 , 0 , True , False , 8 ]

  
# exit

out_arr = np.logical_and (arr1, arr2)

 

print ( "Output Array:" , out_arr)

Output:

  ValueError:  operands could not be broadcast together with shapes (4,) (5,) 

Links:
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.logical_and.html#numpy.logical_and
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