# 多三角三维曲面 使用三角形网格绘制曲面的另外两个示例。 第一个演示使用plot_trisurf的三角形参数,第二个设置Triangulation对象的蒙版并将对象直接传递给plot_trisurf。 ![多三角三维曲面示例](https://matplotlib.org/_images/sphx_glr_trisurf3d_2_001.png) ```python import numpy as np import matplotlib.pyplot as plt import matplotlib.tri as mtri # This import registers the 3D projection, but is otherwise unused. from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused import fig = plt.figure(figsize=plt.figaspect(0.5)) #============ # First plot #============ # Make a mesh in the space of parameterisation variables u and v u = np.linspace(0, 2.0 * np.pi, endpoint=True, num=50) v = np.linspace(-0.5, 0.5, endpoint=True, num=10) u, v = np.meshgrid(u, v) u, v = u.flatten(), v.flatten() # This is the Mobius mapping, taking a u, v pair and returning an x, y, z # triple x = (1 + 0.5 * v * np.cos(u / 2.0)) * np.cos(u) y = (1 + 0.5 * v * np.cos(u / 2.0)) * np.sin(u) z = 0.5 * v * np.sin(u / 2.0) # Triangulate parameter space to determine the triangles tri = mtri.Triangulation(u, v) # Plot the surface. The triangles in parameter space determine which x, y, z # points are connected by an edge. ax = fig.add_subplot(1, 2, 1, projection='3d') ax.plot_trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral) ax.set_zlim(-1, 1) #============ # Second plot #============ # Make parameter spaces radii and angles. n_angles = 36 n_radii = 8 min_radius = 0.25 radii = np.linspace(min_radius, 0.95, n_radii) angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False) angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1) angles[:, 1::2] += np.pi/n_angles # Map radius, angle pairs to x, y, z points. x = (radii*np.cos(angles)).flatten() y = (radii*np.sin(angles)).flatten() z = (np.cos(radii)*np.cos(3*angles)).flatten() # Create the Triangulation; no triangles so Delaunay triangulation created. triang = mtri.Triangulation(x, y) # Mask off unwanted triangles. xmid = x[triang.triangles].mean(axis=1) ymid = y[triang.triangles].mean(axis=1) mask = np.where(xmid**2 + ymid**2 < min_radius**2, 1, 0) triang.set_mask(mask) # Plot the surface. ax = fig.add_subplot(1, 2, 2, projection='3d') ax.plot_trisurf(triang, z, cmap=plt.cm.CMRmap) plt.show() ``` ## 下载这个示例 - [下载python源码: trisurf3d_2.py](https://matplotlib.org/_downloads/trisurf3d_2.py) - [下载Jupyter notebook: trisurf3d_2.ipynb](https://matplotlib.org/_downloads/trisurf3d_2.ipynb)