What is the log2 function in numpy?

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

Syntax

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.

Arguments

The log2 function only accepts the following arguments:

• x: An array-like structure on the contents of which the log2 function will be applied.
• out (optional): The function’s output is stored at this location.
• where (optional): If set True, a universal function is calculated at this position.
• casting (optional): This enables the user to decide how the data will be cast. If set as same_kind, safe casting will take place.
• order (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.
• dtype(optional): This is the data type of the array.
• subok(optional): To pass subclasses, subokmust be set as True.

Return value

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.

Example

The following example demonstrates how to use the log2 function.

To use the log2 function, we first import the numpy library, which contains it.