>>> """
===========================
More triangular 3D surfaces
===========================

Two additional examples of plotting surfaces with triangular mesh.

The first demonstrates use of plot_trisurf's triangles argument, and the
second sets a Triangulation object's mask and passes the object directly
to plot_trisurf.
"""
... 
... import numpy as np
... import matplotlib.pyplot as plt
... import matplotlib.tri as mtri
... 
... 
... 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 = xmid**2 + ymid**2 < min_radius**2
... 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()
...