numpy.logical_xor() in Python

numpy.logical_or() in Python

Last Updated : 29 Nov, 2018

numpy.logical_or(arr1, arr2, out=None, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'logical_or') : This is a logical function and it helps user to find out the truth value of arr1 OR arr2 element-wise. Both the arrays must be of same shape. 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 OR arr2 element-wise(of the same shape).

Code 1 : Working

Python

# Python program explaining
# logical_or() function
import numpy as np

# input
arr1 = [1, 3, False, 4]
arr2 = [3, 0, True, False]

# output
out_arr = np.logical_or(arr1, arr2)

print ("Output Array : ", out_arr)

Output :

Output Array :  [ True  True  True  True]

Code 2 : Value Error if input array's have different shapes

Python

# Python program explaining
# logical_or() function
import numpy as np

# input
arr1 = [8, 2, False, 4]
arr2 = [3, 0, False, False, 8]

# output
out_arr = np.logical_or(arr1, arr2)

print ("Output Array : ", out_arr)

Output :

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

References : https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.logical_or.html#numpy.logical_or .

numpy.logical_xor() in Python

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