Matplotlib 3D Plot Autoscale

Introduction:

Matplotlib is a data visualization library used to create static, animated, and interactive visualizations in Python. Matplotlib provides various plots such as line, scatter, bar, histogram, 3D plots, etc.

This article talks about how to use the Matplotlib 3D plot autoscale feature. Autoscale is an automatic scaling option that adjusts the axes limits based on the data present in the graph.

Procedure:

Matplotlib provides an in-built option to set the autoscale feature for 3D plots.

# Importing the required libraries
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

# Data for the plot
x = np.array([1,2,3,4,5,6,7,8,9,10])
y = np.array([5,6,7,8,2,5,6,3,7,2])
z = np.array([1,2,6,3,2,7,3,3,7,2])

# Creating a 3D plot
fig = plt.figure()
ax = fig.add_subplot(projection='3d')
ax.scatter(x, y, z)

# Setting axis limits to autoscale
ax.autoscale()

# Displaying the plot
plt.show()

In the above code, we imported the libraries numpy and matplotlib to create a 3D plot. We also imported the Axes3D module to create the 3D axis. Then we created three arrays x, y, and z to store the data points.

We created a 3D scatter plot using ax.scatter() and passed the x, y, and z arrays as parameters. Finally, we used the ax.autoscale() function to set the axis limits to autoscale.

Conclusion

In conclusion, Matplotlib provides an in-built option to set the autoscale feature for 3D plots. This feature is helpful when the data points are not uniformly distributed, and we want to adjust the axis limits based on the data present in the graph.

By using the ax.autoscale() function, we can efficiently set the 3D plot's axis limits to autoscale. This helps in improving the overall visualization of the graph, making it more understandable and interpretable.