3D Surface plotting in Python using Matplotlib

Last Updated : 28 Apr, 2025
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A Surface Plot is a representation of three-dimensional dataset. It describes a functional relationship between two independent variables X and Z and a designated dependent variable Y, rather than showing the individual data points. It is a companion plot of the contour plot. It is similar to the wireframe plot, but each face of the wireframe is a filled polygon. This helps to create the topology of the surface which is being visualized.
 

Creating 3D surface Plot


The axes3d present in Matplotlib's mpl_toolkits.mplot3d toolkit provides the necessary functions used to create 3D surface plots.Surface plots are created by using ax.plot_surface() function.
Syntax: 

ax.plot_surface(X, Y, Z)


where X and Y are 2D array of points of x and y while Z is 2D array of heights.Some more attributes of ax.plot_surface() function are listed below:
 

AttributeDescription
X, Y, Z2D arrays of data values
cstridearray of column stride(step size)
rstridearray of row stride(step size)
ccountnumber of columns to be used, default is 50
rcountnumber of row to be used, default is 50
colorcolor of the surface
cmapcolormap for the surface
norminstance to normalize values of color map
vminminimum value of map
vmaxmaximum value of map
facecolorsface color of individual surface
shadeshades the face color


Example: Let's create a 3D surface by using the above function 

Python3 
# Import libraries
from mpl_toolkits import mplot3d
import numpy as np
import matplotlib.pyplot as plt


# Creating dataset
x = np.outer(np.linspace(-3, 3, 32), np.ones(32))
y = x.copy().T # transpose
z = (np.sin(x **2) + np.cos(y **2) )

# Creating figure
fig = plt.figure(figsize =(14, 9))
ax = plt.axes(projection ='3d')

# Creating plot
ax.plot_surface(x, y, z)

# show plot
plt.show()

Output: 


 

Gradient surface Plot


Gradient surface plot is a combination of 3D surface plot with a 2D contour plot. In this plot the 3D surface is colored like 2D contour plot. The parts which are high on the surface contains different color than the parts which are low at the surface.
Syntax:

surf = ax.plot_surface(X, Y, Z, cmap=, linewidth=0, antialiased=False)


The attribute cmap= sets the color of the surface. A color bar can also be added by calling fig.colorbar. The code below create a gradient surface plot:
Example:

Python3 
# Import libraries
from mpl_toolkits import mplot3d
import numpy as np
import matplotlib.pyplot as plt

# Creating dataset
x = np.outer(np.linspace(-3, 3, 32), np.ones(32))
y = x.copy().T # transpose
z = (np.sin(x **2) + np.cos(y **2) )

# Creating figure
fig = plt.figure(figsize =(14, 9))
ax = plt.axes(projection ='3d')

# Creating color map
my_cmap = plt.get_cmap('hot')

# Creating plot
surf = ax.plot_surface(x, y, z,
                       cmap = my_cmap,
                       edgecolor ='none')

fig.colorbar(surf, ax = ax,
             shrink = 0.5, aspect = 5)

ax.set_title('Surface plot')

# show plot
plt.show()

Output: 


 

3D surface Plot having 2D contour plot projections


3D surface plots plotted with Matplotlib can be projected on 2D surfaces. The code below creates a 3D plots and visualizes its projection on 2D contour plot:
Example: 

Python3 
# Import libraries
from mpl_toolkits import mplot3d
import numpy as np
import matplotlib.pyplot as plt

# Creating dataset
x = np.outer(np.linspace(-3, 3, 32), np.ones(32))
y = x.copy().T # transpose
z = (np.sin(x **2) + np.cos(y **2) )

# Creating figure
fig = plt.figure(figsize =(14, 9))
ax = plt.axes(projection ='3d')

# Creating color map
my_cmap = plt.get_cmap('hot')

# Creating plot
surf = ax.plot_surface(x, y, z, 
                       rstride = 8,
                       cstride = 8,
                       alpha = 0.8,
                       cmap = my_cmap)
cset = ax.contourf(x, y, z,
                   zdir ='z',
                   offset = np.min(z),
                   cmap = my_cmap)
cset = ax.contourf(x, y, z,
                   zdir ='x',
                   offset =-5,
                   cmap = my_cmap)
cset = ax.contourf(x, y, z, 
                   zdir ='y',
                   offset = 5,
                   cmap = my_cmap)
fig.colorbar(surf, ax = ax, 
             shrink = 0.5,
             aspect = 5)

# Adding labels
ax.set_xlabel('X-axis')
ax.set_xlim(-5, 5)
ax.set_ylabel('Y-axis')
ax.set_ylim(-5, 5)
ax.set_zlabel('Z-axis')
ax.set_zlim(np.min(z), np.max(z))
ax.set_title('3D surface having 2D contour plot projections')

# show plot
plt.show()

Output: 


Next Article
3D Wireframe plotting in Python using Matplotlib

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