#   
## Overview
The function **`logaddexp()`** of `numpy` in Python returns the logarithm of the sum of exponentiations of `x1` and `x2` inputs in base-2.

It can be expressed mathematically as:

`logaddexp(x1, x2)` = log2($2^{x1}$ + $2^{x2}$)
## Syntax
```
logaddexp2(x1, x2, out)
```
## Parameters 
The `logaddexp2()` function takes the following parameter values:
* **`x1, x2`**: This represents the input arrays or scalers. 
* **`out`**: This represents a location where the result is stored. This is optional.
## Return value
The `logaddexp2()` function returns the logarithm of the sum of the exponentiations of `x1` and `x2` in base-2. 
## Example

from numpy import logaddexp2
# creating our input values
x = 2
y  = 3

# calling the logaddexp2() function
myresult  = logaddexp2(x, y)

print(myresult)

## Explanation
* **Line 1**: We import the  `logaddexp2` from `numpy` module.
* **Lines 3 and 4**: We create variables `x` and `y`.
* **Line 7**: We call the `logaddexp2()` function on the variables `x` and `y`. The result is assigned to a variable `myresult`.
* **Line 9**: We print the variable `myresult`.
## Application
The function `logaddexp2()`  is useful in statistics, especially when the probability of an event is so tiny that it exceeds the range of regular floating-point numbers. In such cases, the logarithm of the calculated probability is stored. The function allows storing the added probabilities in such a fashion.

What is the numpy.logaddexp2() function from NumPy in Python?

Overview

Syntax

Parameters

Return value

Example

Explanation

Application