Create 3D Wireframe Visualizations with Python Matplotlib

Introduction

This lab will guide you through creating a 3D wireframe plot using Python's Matplotlib library. A wireframe plot is a visual representation of a 3D surface where lines are drawn between each point on the surface. This type of plot is useful for visualizing complex 3D data and can be customized to create impressive visualizations.

VM Tips

After the VM startup is done, click the top left corner to switch to the Notebook tab to access Jupyter Notebook for practice.

Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook.

If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

Skills Graph

Import Libraries

The first step is to import the necessary libraries. In this lab, we will use the Matplotlib library to create the wireframe plot and NumPy library to generate the data.

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
import numpy as np

Generate Data

Next, we will generate the data that we will use to create the wireframe plot. In this lab, we will use the np.meshgrid() function to create the X, Y, and Z coordinates.

## Generate data
X, Y = np.meshgrid(np.arange(-5, 5, 0.25), np.arange(-5, 5, 0.25))
R = np.sqrt(X**2 + Y**2)
Z = np.sin(R)

Create the Plot

Now that we have our data, we can create the wireframe plot. In this example, we will use the plot_wireframe() function to create the plot.

## Create the plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_wireframe(X, Y, Z, rstride=5, cstride=5)

Customize the Plot

We can customize the plot to make it more visually appealing. In this example, we will add a title, axis labels, and change the color of the plot.

## Customize the plot
ax.set_title('Wireframe Plot')
ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')
ax.plot_wireframe(X, Y, Z, rstride=5, cstride=5, color='green')

Display the Plot

Finally, we can display the plot using the show() function.

## Display the plot
plt.show()

Summary

In this lab, we learned how to create a 3D wireframe plot using Python's Matplotlib library. We generated the data using NumPy, created the plot using the plot_wireframe() function, and customized the plot to make it more visually appealing. We also learned how to add a title, axis labels, and change the color of the plot. With this knowledge, we can create impressive 3D visualizations of complex data.