#### Squareplus

p
```"""
Squareplus Activation Function

Use Case: Squareplus designed to enhance positive values and suppress negative values.
For more detailed information, you can refer to the following link:
https://en.wikipedia.org/wiki/Rectifier_(neural_networks)#Squareplus
"""

import numpy as np

def squareplus(vector: np.ndarray, beta: float) -> np.ndarray:
"""
Implements the SquarePlus activation function.

Parameters:
vector (np.ndarray): The input array for the SquarePlus activation.
beta (float): size of the curved region

Returns:
np.ndarray: The input array after applying the SquarePlus activation.

Formula: f(x) = ( x + sqrt(x^2 + b) ) / 2

Examples:
>>> squareplus(np.array([2.3, 0.6, -2, -3.8]), beta=2)
array([2.5       , 1.06811457, 0.22474487, 0.12731349])

>>> squareplus(np.array([-9.2, -0.3, 0.45, -4.56]), beta=3)
array([0.0808119 , 0.72891979, 1.11977651, 0.15893419])
"""
return (vector + np.sqrt(vector**2 + beta)) / 2

if __name__ == "__main__":
import doctest

doctest.testmod()
```