""" ====================== Tricontour Smooth User ====================== Demonstrates high-resolution tricontouring on user-defined triangular grids with `matplotlib.tri.UniformTriRefiner`. """ import matplotlib.tri as tri import matplotlib.pyplot as plt import matplotlib.cm as cm 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) cmap = cm.get_cmap(name='terrain', lut=None) ax.tricontourf(tri_refi, z_test_refi, levels=levels, cmap=cmap) 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() ############################################################################# # # ------------ # # References # """""""""" # # The use of the following functions, methods, classes and modules is shown # in this example: import matplotlib matplotlib.axes.Axes.tricontour matplotlib.pyplot.tricontour matplotlib.axes.Axes.tricontourf matplotlib.pyplot.tricontourf matplotlib.tri matplotlib.tri.Triangulation matplotlib.tri.UniformTriRefiner