Bottom Science
Installing Necessary Libraries
Before running the below codes, please make sure you have to install the necessary libraries of python.
Guide to Install Plotting Libraries in Python – Windows/Linux/MacOS
1. Using matplotlib and mplot3d
matplotlib is a popular Python library for creating high-quality visualizations, including 3D plots. mplot3d is a module within matplotlib that provides tools for creating 3D plots. Here’s an example of creating a 3D surface plot using matplotlib and mplot3d:
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
# Create a 3D grid of points
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X**2 + Y**2))
# Plot the surface
ax.plot_surface(X, Y, Z)
# Set the labels and title
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
plt.title('3D Surface Plot')
plt.show()
This code creates a 3D surface plot of the function z = sin(sqrt(x^2 + y^2)). The plot_surface function is used to create the surface, and the set_xlabel, set_ylabel, and set_zlabel functions are used to label the axes. The resulting plot will be displayed using the show function.
2. Using plotly
plotly is a library that provides interactive data visualization tools, including 3D plots. Here’s an example of creating a 3D surface plot using plotly:
import plotly.graph_objects as go
import numpy as np
# Create a 3D grid of points
x = np.linspace(-5, 5, 100)
y = np.linspace(-5, 5, 100)
X, Y = np.meshgrid(x, y)
Z = np.sin(np.sqrt(X**2 + Y**2))
# Create the plot
fig = go.Figure(data=[go.Surface(z=Z, x=X, y=Y)])
# Set the labels and title
fig.update_layout(scene=dict(xaxis_title='X', yaxis_title='Y', zaxis_title='Z'),
title='3D Surface Plot')
fig.show()
3. Using mayavi
mayavi is a Python library for creating 3D scientific visualizations. Here’s an example of creating a 3D surface plot using mayavi:
import numpy as np
from mayavi import mlab
# Create a 3D grid of points
x, y = np.mgrid[-5:5:100j, -5:5:100j]
z = np.sin(np.sqrt(x**2 + y**2))
# Create the plot
mlab.figure(bgcolor=(1,1,1))
surf = mlab.surf(x, y, z)
# Set the labels and title
mlab.xlabel('X')
mlab.ylabel('Y')
mlab.z
This code creates a 3D surface plot of the function z = sin(sqrt(x^2 + y^2)) using plotly. The Surface function is used to create the surface, and the update_layout function is used to label the axes and set the plot title. The resulting plot will be displayed using the show function.
