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

  1. import numpy as np
  2. import matplotlib.pyplot as plt
  3. import matplotlib.tri as mtri
  5. # This import registers the 3D projection, but is otherwise unused.
  6. from mpl_toolkits.mplot3d import Axes3D  # noqa: F401 unused import
  9. fig = plt.figure(figsize=plt.figaspect(0.5))
  11. #============
  12. # First plot
  13. #============
  15. # Make a mesh in the space of parameterisation variables u and v
  16. u = np.linspace(0, 2.0 * np.pi, endpoint=True, num=50)
  17. v = np.linspace(-0.5, 0.5, endpoint=True, num=10)
  18. u, v = np.meshgrid(u, v)
  19. u, v = u.flatten(), v.flatten()
  21. # This is the Mobius mapping, taking a u, v pair and returning an x, y, z
  22. # triple
  23. x = (1 + 0.5 * v * np.cos(u / 2.0)) * np.cos(u)
  24. y = (1 + 0.5 * v * np.cos(u / 2.0)) * np.sin(u)
  25. z = 0.5 * v * np.sin(u / 2.0)
  27. # Triangulate parameter space to determine the triangles
  28. tri = mtri.Triangulation(u, v)
  30. # Plot the surface.  The triangles in parameter space determine which x, y, z
  31. # points are connected by an edge.
  32. ax = fig.add_subplot(1, 2, 1, projection='3d')
  33. ax.plot_trisurf(x, y, z, triangles=tri.triangles, cmap=plt.cm.Spectral)
  34. ax.set_zlim(-1, 1)
  37. #============
  38. # Second plot
  39. #============
  41. # Make parameter spaces radii and angles.
  42. n_angles = 36
  43. n_radii = 8
  44. min_radius = 0.25
  45. radii = np.linspace(min_radius, 0.95, n_radii)
  47. angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
  48. angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
  49. angles[:, 1::2] += np.pi/n_angles
  51. # Map radius, angle pairs to x, y, z points.
  52. x = (radii*np.cos(angles)).flatten()
  53. y = (radii*np.sin(angles)).flatten()
  54. z = (np.cos(radii)*np.cos(3*angles)).flatten()
  56. # Create the Triangulation; no triangles so Delaunay triangulation created.
  57. triang = mtri.Triangulation(x, y)
  59. # Mask off unwanted triangles.
  60. xmid = x[triang.triangles].mean(axis=1)
  61. ymid = y[triang.triangles].mean(axis=1)
  62. mask = np.where(xmid**2 + ymid**2 < min_radius**2, 1, 0)
  63. triang.set_mask(mask)
  65. # Plot the surface.
  66. ax = fig.add_subplot(1, 2, 2, projection='3d')
  67. ax.plot_trisurf(triang, z, cmap=plt.cm.CMRmap)
  70. plt.show()

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