Re: [matplotlib-devel] trisurf plots with independent color data

[Maximilian A. <max...@gm...>]

Hi Byron,

This is a bit of a workaround, but you can specify facecolors explicitly by
creating a triangulation of your surface explicitly and creating a
Poly3DCollection with these facecolors. I'm attaching an example below
which is a modified version of the plot_trisurf demo [1] in the matplotlib
documentation. It showcases both random colors and a smooth gradient (the
latter in the line that's commented out).

I would have thought that it should be possible to pass an argument like
"facecolors" to plot_trisurf directly, since the documentation [2] states
that "other arguments are passed on to Poly3DCollection". However, I
couldn't get this to work quickly. Maybe someone else knows how?

Best regards,
Max

[1] http://matplotlib.org/examples/mplot3d/trisurf3d_demo.html
[2] http://matplotlib.org/mpl_toolkits/mplot3d/api.html



from mpl_toolkits.mplot3d import Axes3D
from matplotlib import cm
import matplotlib.pyplot as plt
import numpy as np

from matplotlib.tri import Triangulation
from mpl_toolkits.mplot3d.art3d import Poly3DCollection

n_angles = 36
n_radii = 8

# An array of radii
# Does not include radius r=0, this is to eliminate duplicate points
radii = np.linspace(0.125, 1.0, n_radii)

# An array of angles
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)

# Repeat all angles for each radius
angles = np.repeat(angles[...,np.newaxis], n_radii, axis=1)

# Convert polar (radii, angles) coords to cartesian (x, y) coords
# (0, 0) is added here. There are no duplicate points in the (x, y) plane
x = np.append(0, (radii*np.cos(angles)).flatten())
y = np.append(0, (radii*np.sin(angles)).flatten())

# Pringle surface
z = np.sin(-x*y)

tri = Triangulation(x, y)  # NOTE: This assumes that there is a nice
projection of the surface into the x/y-plane!
triangle_vertices = np.array([np.array([[x[T[0]], y[T[0]], z[T[0]]],
                                        [x[T[1]], y[T[1]], z[T[1]]],
                                        [x[T[2]], y[T[2]], z[T[2]]]]) for T
in tri.triangles])
midpoints = np.average(triangle_vertices, axis=1)

def find_color_for_point(pt):
    x, y, z = pt
    col = [(y+1)/2, (1-y)/2, 0]
    return col

#facecolors = [find_color_for_point(pt) for pt in midpoints]  # smooth
gradient
facecolors = [np.random.random(3) for pt in midpoints]  # random colors

coll = Poly3DCollection(triangle_vertices, facecolors=facecolors,
edgecolors='black')

fig = plt.figure()
ax = fig.gca(projection='3d')
ax.add_collection(coll)
ax.set_xlim(-1, 1)
ax.set_ylim(-1, 1)
ax.set_zlim(-1, 1)
ax.elev = 50

plt.show()