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).

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### 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
- Get the Median of Numpy Array – (With Examples)
- Numpy – Get Standard Deviation of Array Values
- Numpy – Get Min Value in Array

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