pythonnumpymatplotlibsurfacematplotlib-3d

surface plots in matplotlib

I have a list of 3-tuples representing a set of points in 3D space. I want to plot a surface that covers all these points.

The plot_surface function in the mplot3d package requires as arguments X,Y and Z to be 2d arrays. Is plot_surface the right function to plot surface and how do I transform my data into the required format?

data = [(x1,y1,z1),(x2,y2,z2),.....,(xn,yn,zn)]
Solution

  • For surfaces it's a bit different than a list of 3-tuples, you should pass in a grid for the domain in 2d arrays.

    If all you have is a list of 3d points, rather than some function f(x, y) -> z, then you will have a problem because there are multiple ways to triangulate that 3d point cloud into a surface.

    Here's a smooth surface example:

    import numpy as np
from mpl_toolkits.mplot3d import Axes3D  
# Axes3D import has side effects, it enables using projection='3d' in add_subplot
import matplotlib.pyplot as plt
import random

def fun(x, y):
    return x**2 + y

fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
x = y = np.arange(-3.0, 3.0, 0.05)
X, Y = np.meshgrid(x, y)
zs = np.array(fun(np.ravel(X), np.ravel(Y)))
Z = zs.reshape(X.shape)

ax.plot_surface(X, Y, Z)

ax.set_xlabel('X Label')
ax.set_ylabel('Y Label')
ax.set_zlabel('Z Label')

plt.show()

    3d