A sigmoid function is a mathematical function that has an “S” shaped curve when plotted.

The most common example of a sigmoid function is the logistic sigmoid function, which is calculated as:

**F(x) = 1 / (1 + e ^{-x})**

The easiest way to calculate a sigmoid function in Python is to use the expit() function from the **SciPy** library, which uses the following basic syntax:

from scipy.special import expit #calculate sigmoid function for x = 2.5 expit(2.5)

The following examples show how to use this function in practice.

**Example 1: Calculate Sigmoid Function for One Value**

The following code shows how to calculate the sigmoid function for the value x = 2.5:

from scipy.special import expit #calculate sigmoid function for x = 2.5 expit(2.5) 0.9241418199787566

The value of the sigmoid function for x = 2.5 is **0.924**.

We can confirm this by calculating the value manually:

- F(x) = 1 / (1 + e
^{-x}) - F(x) = 1 / (1 + e
^{-2.5}) - F(x) = 1 / (1 + .082)
- F(x) =
**0.924**

**Example 2: Calculate Sigmoid Function for Multiple Values**

The following code shows how to calculate the sigmoid function for multiple x values at once:

from scipy.special import expit #define list of values values = [-2, -1, 0, 1, 2] #calculate sigmoid function for each value in list expit(values) array([0.11920292, 0.26894142, 0.5, 0.73105858, 0.88079708])

**Example 3: Plot Sigmoid Function for Range of Values**

The following code shows how to plot the values of a sigmoid function for a range of x values using matplotlib:

import matplotlib.pyplot as plt from scipy.special import expit import numpy as np #define range of x-values x = np.linspace(-10, 10, 100) #calculate sigmoid function for each x-value y = expit(x) #create plot plt.plot(x, y) plt.xlabel('x') plt.ylabel('F(x)') #display plot plt.show()

Notice that the plot exhibits the “S” shaped curve that is characteristic of a sigmoid function.

**Additional Resources**

The following tutorials explain how to perform other common operations in Python:

How to Perform Logistic Regression in Python

How to Plot a Logistic Regression Curve in Python

Why we need to consider sigmoid function ? whats the use in practical life ?