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 columns 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
Python3
# Import librariesfrom mpl_toolkits import mplot3dimport numpy as npimport matplotlib.pyplot as plt# Creating datasetx = np.outer(np.linspace(-3, 3, 32), np.ones(32))y = x.copy().T # transposez = (np.sin(x **2) + np.cos(y **2) )# Creating figurefig = plt.figure(figsize =(14, 9))ax = plt.axes(projection ='3d')# Creating plotax.plot_surface(x, y, z)# show plotplt.show() |
Output:
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.