3D Plotting with Matplotlib in Python: Syntax, Examples, and Visualizations

Many situations require visualizing internal relationships between data; using plots can reveal patterns.

The following animated GIFs show how 3‑D visualizations in matplotlib help understand logistic‑regression network performance and the effect of different learning rates on algorithm convergence.

➤01 3D Plot

1. Basic Syntax

After installing matplotlib , the mpl_toolkits.mplot3d module is available automatically.

<code># Importing Libraries
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d

# 3D Plotting
fig = plt.figure()
ax = plt.axes(projection="3d")

# Labeling
ax.set_xlabel('X Axes')
ax.set_ylabel('Y Axes')
ax.set_zlabel('Z Axes')

plt.show()
</code>

2. Python Cmd

Insert the above statements into a Python command line or script.

3. Example

(1) Ex1

<code>#!/usr/local/bin/python
# -*- coding: gbk -*-
# TEST2.PY -- by Dr. ZhuoQing 2020-11-16

from headm import *
from mpl_toolkits.mplot3d import axes3d

ax = plt.axes(projection='3d')
x = [1,2,3,4,5,6,7,8,9]
y = [2,3,4,6,7,8,9,5,1]
z = [5,6,2,4,8,6,5,6,1]
ax.plot3D(x,y,z)
ax.set_xlabel('X Axes')
ax.set_ylabel('Y Axes')
ax.set_zlabel('Z Axes')

plt.show()
</code>

Animated GIF demonstrates the 3D plot.

(2) Ex2

<code>from mpl_toolkits.mplot3d import axes3d

ax = plt.axes(projection='3d')

angle = linspace(0, 2*pi*5, 400)
x = cos(angle)
y = sin(angle)
z = linspace(0, 5, 400)
ax.plot3D(x,y,z)
ax.set_xlabel('X Axes')
ax.set_ylabel('Y Axes')
ax.set_zlabel('Z Axes')

plt.show()
</code>

Animated GIF shows a parametric 3D curve.

(3) Ex3

<code>import matplotlib as mpl
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
import matplotlib.pyplot as plt

mpl.rcParams['legend.fontsize'] = 10

fig = plt.figure()
ax = fig.gca(projection='3d')
theta = np.linspace(-4*np.pi, 4*np.pi, 100)
z = np.linspace(-2, 2, 100)
r = z**2 + 1
x = r * np.sin(theta)
y = r * np.cos(theta)
ax.plot(x, y, z, label='parametric curve')
ax.legend()

plt.show()
</code>

Animated GIF illustrates the 3D parametric curve.

➤02 Scatter Plot

Replace plot3D with scatter to create a 3‑D scatter plot.

<code>from mpl_toolkits.mplot3d import axes3d

ax = plt.axes(projection='3d')

angle = linspace(0, 2*pi*5, 40)
x = cos(angle)
y = sin(angle)
z = linspace(0, 5, 40)
ax.scatter(x, y, z, color='b')
ax.set_xlabel('X Axes')
ax.set_ylabel('Y Axes')
ax.set_zlabel('Z Axes')

plt.show()
</code>

Animated GIF shows the scatter example.

➤03 3D Surface Plot

(1) Ex1

<code>#!/usr/local/bin/python
# -*- coding: gbk -*-
# TEST2.PY -- by Dr. ZhuoQing 2020-11-16

from headm import *
from mpl_toolkits.mplot3d import axes3d

ax = plt.axes(projection='3d')

x = arange(-5, 5, 0.1)
y = arange(-5, 5, 0.1)
x, y = meshgrid(x, y)
R = sqrt(x**2 + y**2)
z = sin(R)
ax.plot_surface(x, y, z)
ax.set_xlabel('X Axes')
ax.set_ylabel('Y Axes')
ax.set_zlabel('Z Axes')

plt.show()
</code>

Animated GIF displays a colored surface.

(2) Example with color map

<code>from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator, FormatStrFormatter
import numpy as np

fig = plt.figure()
ax = fig.gca(projection='3d')

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

# Plot the surface.
surf = ax.plot_surface(X, Y, Z, cmap=cm.coolwarm,
                       linewidth=0, antialiased=False)

# Customize the z axis.
ax.set_zlim(-1.01, 1.01)
ax.zaxis.set_major_locator(LinearLocator(10))
ax.zaxis.set_major_formatter(FormatStrFormatter('%.02f'))

# Add a color bar which maps values to colors.
fig.colorbar(surf, shrink=0.5, aspect=5)

plt.show()
</code>

Animated GIF shows the colored 3‑D surface with a color bar.