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46 lines
1.0 KiB
Python
46 lines
1.0 KiB
Python
"""
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This script demonstrates the implementation of the Sigmoid function.
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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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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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import numpy as np
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def sigmoid(vector: np.ndarray) -> np.ndarray:
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"""
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Implements the sigmoid function
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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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Returns:
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sigmoid_vec (np.array): The input numpy array, after applying
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sigmoid.
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Examples:
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>>> sigmoid(np.array([-1.0, 1.0, 2.0]))
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array([0.26894142, 0.73105858, 0.88079708])
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>>> sigmoid(np.array([0.0]))
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array([0.5])
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>>> sigmoid(np.array([100.0]))
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array([1.])
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>>> sigmoid(np.array([-100.0]))
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array([3.72007598e-44])
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"""
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return 1 / (1 + np.exp(-vector))
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if __name__ == "__main__":
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import doctest
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doctest.testmod()
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