matplotlib中的曲面图 [英] surface plots in matplotlib

问题描述

我有一个3元组的列表，表示3D空间中的一组点.我想绘制一个覆盖所有这些点的表面.

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.

mplot3d包中的plot_surface函数要求X，Y和Z作为2d数组作为参数. plot_surface是用于绘制表面的正确函数吗?如何将数据转换为所需的格式?

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)]

推荐答案

对于曲面，它与3元组列表有点不同，您应该在2d数组中为该域传递网格.

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.

如果您拥有的只是3d点列表，而不是某些函数f(x, y) -> z，那么您将遇到问题，因为有多种方法可以将3d点云三角化为曲面.

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.

这是一个光滑的表面示例:

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()

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