Interactive animation with widgets in Matplotlib - Mini Project: Build & Apply

Interactive Animation with Widgets

📖 Scenario: You are working on a simple data visualization project where you want to animate a sine wave and control its frequency interactively using a slider widget. This will help you understand how changing parameters affect the wave in real time.

🎯 Goal: Build an interactive sine wave animation using matplotlib and a slider widget to control the frequency of the wave.

📋 What You'll Learn

Create a time array for the sine wave

Set an initial frequency value

Create an animation function that updates the sine wave

Add a slider widget to control the frequency interactively

Display the animated plot with the slider

💡 Why This Matters

🌍 Real World

Interactive animations help in exploring data and understanding how changing parameters affect results in real time, useful in education and presentations.

💼 Career

Data scientists and analysts often create interactive visualizations to communicate insights clearly and allow stakeholders to explore data dynamically.

1

Create the time array for the sine wave

Create a variable called t that is a NumPy array of 100 values evenly spaced between 0 and 2 * pi.

Matplotlib

# Create the time array 't' with 100 points from 0 to 2 * pi
# Your code here

Need a hint?

Use np.linspace to create evenly spaced values.

2

Set the initial frequency value

Create a variable called freq and set it to 1. This will be the initial frequency of the sine wave.

Matplotlib

import numpy as np

t = np.linspace(0, 2 * np.pi, 100)

# Set the initial frequency 'freq' to 1
# Your code here

Need a hint?

Just assign the number 1 to the variable freq.

3

Create the animation function and plot setup

Import matplotlib.pyplot as plt and matplotlib.animation as animation. Create a figure and axis using plt.subplots(). Plot the initial sine wave using ax.plot(t, np.sin(freq * t)) and save the line object as line. Define a function called update that takes a frame number frame and updates the y-data of line to np.sin(freq * t + 0.1 * frame). Create an animation object called ani using animation.FuncAnimation with the figure, update function, and 100 frames.

Matplotlib

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

t = np.linspace(0, 2 * np.pi, 100)
freq = 1

# Create figure and axis
# Plot initial sine wave and save line object
# Define update function to animate the sine wave
# Create animation object
# Your code here

Need a hint?

Use plt.subplots() to create the plot and animation.FuncAnimation to animate.

4

Add a slider widget to control frequency interactively

Import matplotlib.widgets.Slider. Create a slider axis below the plot using plt.axes([0.25, 0.02, 0.50, 0.03]). Create a slider called freq_slider with label 'Frequency', minimum 0.1, maximum 5, and initial value freq. Define a function called update_freq that takes a value val, updates the global variable freq to val, and updates the y-data of line to np.sin(freq * t). Connect freq_slider.on_changed(update_freq). Finally, call plt.show() to display the interactive plot.

Matplotlib

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from matplotlib.widgets import Slider

t = np.linspace(0, 2 * np.pi, 100)
freq = 1

fig, ax = plt.subplots()
line, = ax.plot(t, np.sin(freq * t))

ax.set_ylim(-1.5, 1.5)

def update(frame):
    line.set_ydata(np.sin(freq * t + 0.1 * frame))
    return line,

ani = animation.FuncAnimation(fig, update, frames=100, blit=True)

# Create slider axis and slider widget
# Define update_freq function to update frequency and line data
# Connect slider to update_freq
# Show the plot
# Your code here

Need a hint?

Use Slider to add the slider and connect it with on_changed.