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NumPy bitwise_or() function

In this tutorial, we will cover the bitwise_or binary operation of the Numpy library.

In Numpy, the bitwise_or() function is mainly used to perform the bitwise_or operation.

  • This function will calculate the bit-wise OR of two arrays, element-wise.

  • The bitwise_or() function calculates the bit-wise OR of the underlying binary representation of the integers in the input array.

  • It is important to note that if one of the corresponding bit in the operands is 1 then the resultant bit in the output of the OR operation will be set to 1, otherwise it will be set to 0.

Given below is the truth table of OR operation where you will see the OR result of the two bits is 1 if one of the bits is 1 otherwise the result will be 0.

Numpy bitwise_or function

Syntax of bitwise_or():

The syntax required to use this function is as follows:

numpy.bitwise_or(x1, x2, /, out, *, where=True, casting='same_kind', order='K', dtype, subok=True[, signature, extobj]) = <ufunc 'bitwise_or'>

Parameters:

let us now take a look at the parameters of this function:

  • x1, x2
    These two are input arrays and with this function, only integer and boolean types are handled. If x1.shape != x2.shape, then they must be broadcastable to a common shape (and this shape will become the shape of the output).

  • out
    This parameter mainly indicates a location in which the result is stored. If this parameter is provided, it must have a shape that the inputs broadcast to. If this parameter is either not provided or it is None then a freshly-allocated array is returned.

  • where
    This parameter is used to indicate a condition that is broadcast over the input. At those locations where the condition is True, the out array will be set to the ufunc result, else the out array will retain its original value.

Returned Values:

This function will return a scalar if both x1 and x2 are scalars.

Example 1:

In the example below, we will illustrate the usage of the bitwise_or() function:

import numpy as np

num1 = 15
num2 = 20
 
print ("The Input  number1 is: ", num1)
print ("The Input  number2 is: ", num2) 
   
output = np.bitwise_or(num1, num2) 
print ("The bitwise_or of 15 and 20 is: ", output) 


The input number1 is: 15
The input number2 is: 20
The bitwise_or of 15 and 20 is: 31

Example 2:

In the example below, we will use the bitwise_or() function with two arrays:

import numpy as np
 
ar1 = [2, 8, 135]
ar2 = [3, 5, 115]
  
print ("The Input array1 is : ", ar1) 
print ("The Input array2 is : ", ar2)
   
output_arr = np.bitwise_or(ar1, ar2) 
print ("The Output array after bitwise_or:", output_arr)


The Input array1 is : [2, 8, 135]
The Input array2 is : [3, 5, 115]
The Output array after bitwise_or: [ 3 13 247]

Summary

In this tutorial, we covered the bitwise_or() function of the NumPy library. We covered its basic syntax and parameters and then the values returned by this function along with multiple code examples.