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+ """
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+ This script demonstrates the implementation of the Sigmoid function.
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+
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+ The function takes a vector of K real numbers as input and then 1 / (1 + exp(-x)).
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+ After through Sigmoid, the element of the vector mostly 0 between 1. or 1 between -1.
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+
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+ Script inspired from its corresponding Wikipedia article
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+ https://en.wikipedia.org/wiki/Sigmoid_function
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+ """
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+
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+ import numpy as np
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+
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+
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+ def sigmoid (vector : float ):
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+ """
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+ Implements the sigmoid function
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+
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+ Parameters:
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+ vector (np.array): A numpy array of shape (1,n)
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+ consisting of real values
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+
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+
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+ Returns:
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+ sigmoid_vec (np.array): The input numpy array, after applying
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+ sigmoid.
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+
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+ >>> vec = np.array([-1.0, 1.0, 2.0])
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+ >>> sigmoid(vec)
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+ array([0.26894142, 0.73105858, 0.88079708])
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+ """
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+
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+ return 1 / (1 + np .exp (- vector ))
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+
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+
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+ if __name__ == "__main__" :
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+ print (
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+ sigmoid (np .array ([- 1.0 , 1.0 , 2.0 ]))
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+ ) # --> [0.26894142, 0.73105858, 0.88079708]
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