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Tricontour Lisse N° d'utilisateur
Démontre le tricontouring haute résolution sur des grilles triangulaires définies par l'utilisateur avec matplotlib.tri.UniformTriRefiner
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import matplotlib.tri as tri
import matplotlib.pyplot as plt
import numpy as np
# ----------------------------------------------------------------------------
# Analytical test function
# ----------------------------------------------------------------------------
def function_z(x, y):
r1 = np.sqrt((0.5 - x)**2 + (0.5 - y)**2)
theta1 = np.arctan2(0.5 - x, 0.5 - y)
r2 = np.sqrt((-x - 0.2)**2 + (-y - 0.2)**2)
theta2 = np.arctan2(-x - 0.2, -y - 0.2)
z = -(2 * (np.exp((r1 / 10)**2) - 1) * 30. * np.cos(7. * theta1) +
(np.exp((r2 / 10)**2) - 1) * 30. * np.cos(11. * theta2) +
0.7 * (x**2 + y**2))
return (np.max(z) - z) / (np.max(z) - np.min(z))
# ----------------------------------------------------------------------------
# Creating a Triangulation
# ----------------------------------------------------------------------------
# First create the x and y coordinates of the points.
n_angles = 20
n_radii = 10
min_radius = 0.15
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 = function_z(x, y)
# Now create the Triangulation.
# (Creating a Triangulation without specifying the triangles results in the
# Delaunay triangulation of the points.)
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)
# ----------------------------------------------------------------------------
# Refine data
# ----------------------------------------------------------------------------
refiner = tri.UniformTriRefiner(triang)
tri_refi, z_test_refi = refiner.refine_field(z, subdiv=3)
# ----------------------------------------------------------------------------
# Plot the triangulation and the high-res iso-contours
# ----------------------------------------------------------------------------
fig, ax = plt.subplots()
ax.set_aspect('equal')
ax.triplot(triang, lw=0.5, color='white')
levels = np.arange(0., 1., 0.025)
ax.tricontourf(tri_refi, z_test_refi, levels=levels, cmap='terrain')
ax.tricontour(tri_refi, z_test_refi, levels=levels,
colors=['0.25', '0.5', '0.5', '0.5', '0.5'],
linewidths=[1.0, 0.5, 0.5, 0.5, 0.5])
ax.set_title("High-resolution tricontouring")
plt.show()
Références
L'utilisation des fonctions, méthodes, classes et modules suivants est illustrée dans cet exemple :