Version 3.0.2
matplotlib
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Triangular 3D filled contour plotΒΆ

Filled contour plots of unstructured triangular grids.

The data used is the same as in the second plot of trisurf3d_demo2. tricontour3d_demo shows the unfilled version of this example.

../../_images/sphx_glr_tricontourf3d_001.png
# This import registers the 3D projection, but is otherwise unused.
from mpl_toolkits.mplot3d import Axes3D  # noqa: F401 unused import

import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np

# First create the x, y, z coordinates of the points.
n_angles = 48
n_radii = 8
min_radius = 0.25

# Create the mesh in polar coordinates and compute x, y, z.
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

x = (radii*np.cos(angles)).flatten()
y = (radii*np.sin(angles)).flatten()
z = (np.cos(radii)*np.cos(3*angles)).flatten()

# Create a custom triangulation.
triang = tri.Triangulation(x, y)

# Mask off unwanted triangles.
triang.set_mask(np.hypot(x[triang.triangles].mean(axis=1),
                         y[triang.triangles].mean(axis=1))
                < min_radius)

fig = plt.figure()
ax = fig.gca(projection='3d')
ax.tricontourf(triang, z, cmap=plt.cm.CMRmap)

# Customize the view angle so it's easier to understand the plot.
ax.view_init(elev=45.)

plt.show()

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