Introduction to Animations - ( Matplotlib Animations )

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Syntax

animation.FuncAnimation(fig, func, frames=None, init_func=None, fargs=None, save_count=None, **kwargs)

Example

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation

fig, ax = plt.subplots()

def animate(i):
    ax.clear()
    x = np.arange(0, 2*np.pi, 0.01)
    y = np.sin(x + i / 10.0)
    ax.plot(x, y)

ani = animation.FuncAnimation(fig, animate, frames=100, repeat=True)
plt.show()

Output

The output of the above example will be an animated sine wave plot that changes its phase over time.

Explanation

Creating animations is a great way to visualize dynamic data and understand how it changes over time. Matplotlib provides the animation module that can be used to create animations in Python.

The animation.FuncAnimation() function is used to create an animation. It takes in the figure, a function that will be called at each frame, the number of frames to be displayed, and other optional arguments such as the initialization function.

In the above example, we create an animated sine wave plot that changes its phase over time. We first create a figure and an axis object. The animate() function is defined to update the plot at each frame. The FuncAnimation() function is then called with the figure, the animate() function, and the number of frames as arguments.

Use

Animations can be used to visualize dynamic data such as stock prices, weather patterns, traffic patterns, etc. They can help to understand how the data changes over time and to identify patterns and trends.

Important Points

• Matplotlib provides the animation module for creating animations in Python
• The animation.FuncAnimation() function is used to create an animation
• It takes in the figure, a function that will be called at each frame, the number of frames, and other optional arguments such as the initialization function
• Animations can be used to visualize dynamic data and identify patterns and trends

Summary

In conclusion, the animation module in Matplotlib provides a powerful way to create dynamic visualizations of data in Python. The animation.FuncAnimation() function can be used to create animations by taking in the figure, a function that will be called at each frame, the number of frames, and other optional arguments. Animations are useful for visualizing dynamic data and identifying patterns and trends.