mirror of
https://github.com/TheAlgorithms/Python.git
synced 2024-11-24 21:41:08 +00:00
36 lines
857 B
Python
36 lines
857 B
Python
|
"""
|
||
|
|
This script demonstrates the implementation of the Binary Step function.
|
||
|
|
|
||
|
|
It's an activation function in which the neuron is activated if the input is positive
|
||
|
|
or 0, else it is deactivated
|
||
|
|
|
||
|
|
It's a simple activation function which is mentioned in this wikipedia article:
|
||
|
|
https://en.wikipedia.org/wiki/Activation_function
|
||
|
|
"""
|
||
|
|
|
||
|
|
import numpy as np
|
||
|
|
|
||
|
|
|
||
|
|
def binary_step(vector: np.ndarray) -> np.ndarray:
|
||
|
|
"""
|
||
|
|
Implements the binary step function
|
||
|
|
|
||
|
|
Parameters:
|
||
|
|
vector (ndarray): A vector that consists of numeric values
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
vector (ndarray): Input vector after applying binary step function
|
||
|
|
|
||
|
|
>>> vector = np.array([-1.2, 0, 2, 1.45, -3.7, 0.3])
|
||
|
|
>>> binary_step(vector)
|
||
|
|
array([0, 1, 1, 1, 0, 1])
|
||
|
|
"""
|
||
|
|
|
||
|
|
return np.where(vector >= 0, 1, 0)
|
||
|
|
|
||
|
|
|
||
|
|
if __name__ == "__main__":
|
||
|
|
import doctest
|
||
|
|
|
||
|
|
doctest.testmod()
|