In numpy, a library of the high-level programming language Python, we can use the ** log2** function to calculate the base 2 logarithm.

The `numpy`

library must be imported to use the `log2`

function:

```
import numpy as np
```

```
np.log2(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])= <ufunc 'log2'>
```

A universal function (

`ufunc`

) is a function that operates on ndarrays in an element-by-element fashion. The`log2`

method is a universal function.

The `log2`

function only accepts the following arguments:

: An array-like structure on the contents of which the`x`

`log2`

function will be applied.(optional): The function’s output is stored at this location.`out`

(optional): If set`where`

`True`

, a universal function is calculated at this position.(optional): This enables the user to decide how the data will be cast. If set as`casting`

*same_kind*, safe casting will take place.(optional): This determines the memory layout of the output. For example, if set as K, the function reads data in the order they are written in memory.`order`

(optional): This is the data type of the array.`dtype`

(optional): To pass subclasses,`subok`

`subok`

must be set as`True`

.

The `log2`

function returns an array of `float`

values whose imaginary part lies in `[-pi,pi]`

.

If a number can not be represented as a real number or infinity, it returns `nan`

, and the invalid floating point error flag is set. The `log2`

function has branch cuts at [-inf,0] and is continuous above it for complex input.

For real input, the `log2`

function returns real input. It treats the floating-point negative zero as an infinitesimal negative number, following the C99 standard.

If

`x`

is scalar, then return type is scalar.

The following example demonstrates how to use the `log2`

function.

To use the `log2`

function, we first import the `numpy`

library, which contains it.

import numpy as npprint(np.log2([0, 1, 4, 6]))

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