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"""

This script demonstrates the implementation of the Sigmoid function.

The function takes a vector of K real numbers as input and then 1 / (1 + exp(-x)).

After through Sigmoid, the element of the vector mostly 0 between 1. or 1 between -1.

Script inspired from its corresponding Wikipedia article

https://en.wikipedia.org/wiki/Sigmoid_function

"""

import numpy as np

def sigmoid(vector: np.array) -> np.array:

"""

Implements the sigmoid function

Parameters:

vector (np.array): A numpy array of shape (1,n)

consisting of real values

Returns:

sigmoid_vec (np.array): The input numpy array, after applying

sigmoid.

Examples:

>>> sigmoid(np.array([-1.0, 1.0, 2.0]))

array([0.26894142, 0.73105858, 0.88079708])

>>> sigmoid(np.array([0.0]))

array([0.5])

"""

return 1 / (1 + np.exp(-vector))

if __name__ == "__main__":

import doctest

doctest.testmod()

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