Function test_computed_zorder

lib/mpl_toolkits/mplot3d/tests/test_axes3d.py:2213–2292

()

@image_comparison(['computed_zorder.png'], remove_text=True, style='mpl20')
def test_computed_zorder():
    plt.rcParams['axes3d.automargin'] = True  # Remove when image is regenerated
    fig = plt.figure()
    ax1 = fig.add_subplot(221, projection='3d')
    ax2 = fig.add_subplot(222, projection='3d')
    ax2.computed_zorder = False

    # create a horizontal plane
    corners = ((0, 0, 0), (0, 5, 0), (5, 5, 0), (5, 0, 0))
    for ax in (ax1, ax2):
        tri = art3d.Poly3DCollection([corners],
                                     facecolors='white',
                                     edgecolors='black',
                                     zorder=1)
        ax.add_collection3d(tri)

        # plot a vector
        ax.plot((2, 2), (2, 2), (0, 4), c='red', zorder=2)

        # plot some points
        ax.scatter((3, 3), (1, 3), (1, 3), c='red', zorder=10)

        ax.set_xlim(0, 5.0)
        ax.set_ylim(0, 5.0)
        ax.set_zlim(0, 2.5)

    ax3 = fig.add_subplot(223, projection='3d')
    ax4 = fig.add_subplot(224, projection='3d')
    ax4.computed_zorder = False

    dim = 10
    X, Y = np.meshgrid((-dim, dim), (-dim, dim))
    Z = np.zeros((2, 2))

    angle = 0.5
    X2, Y2 = np.meshgrid((-dim, dim), (0, dim))
    Z2 = Y2 * angle
    X3, Y3 = np.meshgrid((-dim, dim), (-dim, 0))
    Z3 = Y3 * angle

    r = 7
    M = 1000
    th = np.linspace(0, 2 * np.pi, M)
    x, y, z = r * np.cos(th),  r * np.sin(th), angle * r * np.sin(th)
    for ax in (ax3, ax4):
        ax.plot_surface(X2, Y3, Z3,
                        color='blue',
                        alpha=0.5,
                        linewidth=0,
                        zorder=-1)
        ax.plot(x[y < 0], y[y < 0], z[y < 0],
                lw=5,
                linestyle='--',
                color='green',
                zorder=0)

        ax.plot_surface(X, Y, Z,
                        color='red',