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Triangular 3D filled contour plot — Matplotlib 3.12.0.dev738+ge3fc0dad9 documentation
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Triangular 3D filled contour plot#

Filled contour plots of unstructured triangular grids.

The data used is the same as in the second plot of More triangular 3D surfaces. Triangular 3D contour plot shows the unfilled version of this example.

import matplotlib.pyplot as plt
import numpy as np

import matplotlib.tri as tri

# 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)

ax = plt.figure().add_subplot(projection='3d')
ax.tricontourf(triang, z, cmap="CMRmap")

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

plt.show()
tricontourf3d [tricontourf3d]

Tags: plot-type: 3D plot-type: specialty level: intermediate

Total running time of the script: (0 minutes 1.539 seconds)

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