.. _mplot3d-trisurf3d_demo2:

mplot3d example code: trisurf3d_demo2.py
========================================



.. plot:: /home/tcaswell/source/p/matplotlib/doc/mpl_examples/mplot3d/trisurf3d_demo2.py

::

    '''
    ===========================
    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
    from mpl_toolkits.mplot3d import Axes3D
    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(angles*3.0)).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()
    

Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)