When working with a collection of 3D points represented as 3-tuples, it is not immediately clear if the plot_surface function is the ideal option for surface plotting. Let's delve into the nuances and find out how to prepare the data for this function.
plot_surface requires X, Y, and Z to be 2D arrays. Unlike a surface plot from a function f(x, y) -> z, where you can provide a grid domain, a point cloud presents a challenge as it requires triangulation.
Since your data is a list of 3D points, you'll need to convert it into a format that plot_surface can understand. One approach is to use meshgrid to create a grid domain, as demonstrated in the following code snippet:
<code class="python">import numpy as np data = [(x1,y1,z1),(x2,y2,z2),.....,(xn,yn,zn)] x, y = zip(*data) # Extract x and y coordinates from the tuples X, Y = np.meshgrid(x, y) # Create a grid domain for X and Y # Convert the z coordinates into a 2D array zs = np.array([z for x, y, z in data]).reshape(X.shape)</code>
Now, you have X, Y, and Z in the required 2D array format.
With the data ready, you can proceed with plotting the surface using plot_surface:
<code class="python">from mpl_toolkits.mplot3d import Axes3D # Enable 3D plotting import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_subplot(111, projection='3d') # Create a 3D subplot ax.plot_surface(X, Y, Z)</code>
This should generate a smooth surface passing through the given points.
The above is the detailed content of Here are a few question-based titles that fit the article content: * How can I plot a surface from a collection of 3D points using Matplotlib\'s `plot_surface` function? * Plotting Surfaces in Matplo. For more information, please follow other related articles on the PHP Chinese website!