I have 3d vertex position data (x,y,z), scalar values at each vertex v, and vertex indices for each triangle tri.
If I were to draw the surface geometry itself, I could use plot_trisurf. If I were to draw a 2D projected plot with each triangle colored according to the vertex scalar, than I could use tripcolor with one of the coordinates omitted. However, it seems oddly unclear how I draw the 3D surface with each face colored according to the vertex scalar, not the z coordinate value.
How do I do this? If it is not within matplotlib's ability, is there a python tool that can do this?
You can manually create the faces from triangle indices and color them based on your scalar values.
import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d.art3d import Poly3DCollection
from matplotlib import cm
# Example data
# Vertex coordinates
x = np.array([0, 1, 0, 1])
y = np.array([0, 0, 1, 1])
z = np.array([0, 0, 0, 1])
v = np.array([0.1, 0.5, 0.9, 0.6]) # Scalar values at each vertex
# Triangle definitions (vertex indices)
tri = np.array([
[0, 1, 2],
[1, 2, 3]
])
# Create triangle vertices for plotting
verts = [list(zip(x[t], y[t], z[t])) for t in tri]
# Compute average scalar for each face for coloring
face_colors = np.mean(v[tri], axis=1)
# Normalize for colormap
norm = plt.Normalize(v.min(), v.max())
colors = cm.viridis(norm(face_colors))
# Plot
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
mesh = Poly3DCollection(verts, facecolors=colors, edgecolors='k', linewidths=0.5)
ax.add_collection3d(mesh)
ax.auto_scale_xyz(x, y, z)
plt.colorbar(cm.ScalarMappable(norm=norm, cmap='viridis'), ax=ax, label='Scalar value')
plt.show()