Get Log2 of Each Element in Numpy Array

The Numpy library in Python comes with a number of built-in functions to perform common mathematical operations on arrays. In this tutorial, we will look at one such function that helps us get the element-wise log2 (logarithm with base 2) of a Numpy array with the help of some examples.

How to get the log2 of values in a Numpy array?

You can use the numpy.log2() function to get the log2 (logarithm with base 2) of each element in a Numpy array. Pass the array as an argument.

The following is the syntax –

numpy.log2(ar)

It returns an array containing the base 2 logarithm of each element in the passed array.

Let’s now look at a step-by-step example of using the numpy.log2() function.

Step 1 – Create a Numpy array

First, we will create a Numpy array that we will use throughout this tutorial.

import numpy as np

# create numpy array
e = np.exp(1)
ar = np.array([1, 2, 4, 6, 8])
# display the array
print(ar)

Output:

[1 2 4 6 8]

Here, we used the numpy.array() function to create a Numpy array containing some numbers. You can see that the array contains some integers (note that there are some values that are powers of two – 2, 4, and 8).

Step 2 – Get the log2 using numpy.log2()

To get the base 2 log of each element in a Numpy array, pass the array as an argument to the numpy.log2() function.

Let’s get the base 2 log for the array created above.

# get the log2 of each element
np.log2(ar)

Output:

array([0.       , 1.       , 2.       , 2.5849625, 3.       ])

We get a Numpy array with the base 2 logarithm value of each element in the array ar.

The numpy.log2() function works similarly on higher-dimensional arrays. For example, let’s apply this function to a 2D array of some numbers.

# create 2D numpy array
e = np.exp(1)
ar = np.array([[1, 2, 1],
               [4, 10, 4],
               [5, 8, 6]])
# get the log2 of each element
np.log2(ar)

Output:

array([[0.        , 1.        , 0.        ],
       [2.        , 3.32192809, 2.        ],
       [2.32192809, 3.        , 2.5849625 ]])

You can see that we get the base 2 log value of each element in the 2D array.

For more on the numpy.log2() function, refer to its documentation.

You might also be interested in –

• Numpy – Get the Sign of Each Element in Array
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• Numpy – Get Standard Deviation of Array Values
• Numpy – Get Min Value in Array