importmatplotlib.pyplotaspltimportnumpyasnpimportmatplotlib.triasmtrifig=plt.figure(figsize=plt.figaspect(0.5))# ==========# First plot# ==========# Make a mesh in the space of parameterisation variables u and vu=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# triplex=(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 trianglestri=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="Spectral")ax.set_zlim(-1,1)# ===========# Second plot# ===========# Make parameter spaces radii and angles.n_angles=36n_radii=8min_radius=0.25radii=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**2triang.set_mask(mask)# Plot the surface.ax=fig.add_subplot(1,2,2,projection='3d')ax.plot_trisurf(triang,z,cmap="CMRmap")plt.show()

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