How to Create a Surface Plot in Matplotlib with a List of 3D Points?

Surface Plots in Matplotlib

When creating a surface plot, the plot_surface function requires 2D arrays as arguments to represent the points in 3D space. However, if you only have a list of 3D points, there are specific considerations to take.

Triangulating Point Clouds

For a list of 3D points, plot_surface cannot be used directly due to the ambiguity in triangulating the points into a surface. Matplotlib does not provide a method to automatically triangulate points into a surface.

Alternative Approach: Grid-Based Surface

If you do not have a function representing the surface, you can generate a grid-based surface using a function like fun(x, y). In this approach, you define a meshgrid of points and compute the corresponding z-values using the given function.

<code class="python">import numpy as np
import matplotlib.pyplot as plt

# Define the function
def fun(x, y):
    return x**2 + y

# Create a meshgrid
x = y = np.arange(-3.0, 3.0, 0.05)
X, Y = np.meshgrid(x, y)

# Compute the z-values
zs = np.array(fun(np.ravel(X), np.ravel(Y)))
Z = zs.reshape(X.shape)

# Create the surface plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
ax.plot_surface(X, Y, Z)</code>

This approach allows you to create a smooth surface that passes through the given 3D points and covers the entire extent of the grid.

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