Matplotlib "patch" like function for 3D triangular meshes

Question

I would like to plot a 3D finite element mesh using MATPLOTLIB. I have some problems using MAYAVI, so this kind of solution does not apply.

I need something like Matlab "patch" function, as shown below:

x = [0.0, 1.0, 0.0];
y = [0.0, 0.0, 1.0];
z = [0.0, 1.0, 1.0];
v = 100.0;
view(3)
patch(x, y, z, v)
hold on;
x = [1.0, 1.0, 0.0];
y = [0.0, 1.0, 1.0];
z = [1.0, 0.0, 1.0];
v = 50.0;
patch(x, y, z, v)

in this code, "v" is the scalar field evaluated at the center of each triangle. It produces the image below.

I think this is exactly what you need and so a possible duplicate question. — user6764549
– user6764549, Commented Jul 4, 2018 at 0:35
No, it is not. In this post, only the surface is plotted. I need to use color gradients to represent the scalar vector. — Gabs
– Gabs, Commented Jul 4, 2018 at 0:38
The OP in his question has included an updated answer which has added color tri.set_color(colors.rgb2hex(sp.rand(3))). — user6764549
– user6764549, Commented Jul 4, 2018 at 0:53

jedwards · Accepted Answer · 2018-07-04 00:49:14Z

The following code produces similar results, but you'll want to play around with some of the parameters (colormap, normalization range (vmin, vmax), view angle, axis tick locations) to get exactly what you want:

import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.art3d import Poly3DCollection


def patch(ax, x, y, z, v, vmin=0, vmax=100, cmap_name='viridis'):
    cmap = mpl.cm.get_cmap(cmap_name)               # Get colormap by name
    c = cmap(mpl.colors.Normalize(vmin, vmax)(v))   # Normalize value and get color
    pc = Poly3DCollection([list(zip(x,y,z))])       # Create PolyCollection from coords
    pc.set_facecolor(c)                             # Set facecolor to mapped value
    pc.set_edgecolor('k')                           # Set edgecolor to black
    ax.add_collection3d(pc)                         # Add PolyCollection to axes
    return pc

def view(ax, code):
    if code == 2: #view(2) sets the default two-dimensional view, az = 0, el = 90.
        ax.view_init(90, 0)     # (args are reversed from MATLAB)

    if code == 3: #view(3) sets the default three-dimensional view, az = –37.5, el = 30.
        ax.view_init(30, -37.5)


fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')

x = [0.0, 1.0, 0.0];
y = [0.0, 0.0, 1.0];
z = [0.0, 1.0, 1.0];
v = 100.0;

patch(ax, x, y, z, v)

x = [1.0, 1.0, 0.0];
y = [0.0, 1.0, 1.0];
z = [1.0, 0.0, 1.0];
v = 50.0;
patch(ax, x, y, z, v)

view(ax, 3)
plt.show()

Produces:

(The image at the top of the answer is rotated to get a similar view to yours in the question, because something seems off).

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