3D Surface plotting in Python using Matplotlib

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:

Attribute Description
X, Y, Z 2D arrays of data values
cstride array of column stride(step size)
rstride array of row stride(step size)
ccount number of colums to be used, default is 50
rcount number of row to be used, default is 50
color color of the surface
cmap colormap for the surface
norm instance to normalize values of color map
vmin minimum value of map
vmax maximum value of map
facecolors face color of individual surface
shade shades the face color

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



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# 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 figyre
fig = plt.figure(figsize =(14, 9))
ax = plt.axes(projection ='3d')
  
# Creating plot
ax.plot_surface(x, y, z)
  
# show plot
plt.show()

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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= stes 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:

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# 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 figyre
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()

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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:

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code

# 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 figyre
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()

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Output:




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