.. _pylab_examples-triplot_demo: pylab_examples example code: triplot_demo.py ============================================ .. plot:: /home/tcaswell/src/p/matplotlib/doc/mpl_examples/pylab_examples/triplot_demo.py :: """ Creating and plotting unstructured triangular grids. """ import matplotlib.pyplot as plt import matplotlib.tri as tri import numpy as np import math # Creating a Triangulation without specifying the triangles results in the # Delaunay triangulation of the points. # First create the x and y coordinates of the points. n_angles = 36 n_radii = 8 min_radius = 0.25 radii = np.linspace(min_radius, 0.95, n_radii) angles = np.linspace(0, 2*math.pi, n_angles, endpoint=False) angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1) angles[:, 1::2] += math.pi/n_angles x = (radii*np.cos(angles)).flatten() y = (radii*np.sin(angles)).flatten() # Create the Triangulation; no triangles so Delaunay triangulation created. triang = tri.Triangulation(x, y) # Mask off unwanted triangles. xmid = x[triang.triangles].mean(axis=1) ymid = y[triang.triangles].mean(axis=1) mask = np.where(xmid*xmid + ymid*ymid < min_radius*min_radius, 1, 0) triang.set_mask(mask) # Plot the triangulation. plt.figure() plt.gca().set_aspect('equal') plt.triplot(triang, 'bo-', lw=1) plt.title('triplot of Delaunay triangulation') # You can specify your own triangulation rather than perform a Delaunay # triangulation of the points, where each triangle is given by the indices of # the three points that make up the triangle, ordered in either a clockwise or # anticlockwise manner. xy = np.asarray([ [-0.101, 0.872], [-0.080, 0.883], [-0.069, 0.888], [-0.054, 0.890], [-0.045, 0.897], [-0.057, 0.895], [-0.073, 0.900], [-0.087, 0.898], [-0.090, 0.904], [-0.069, 0.907], [-0.069, 0.921], [-0.080, 0.919], [-0.073, 0.928], [-0.052, 0.930], [-0.048, 0.942], [-0.062, 0.949], [-0.054, 0.958], [-0.069, 0.954], [-0.087, 0.952], [-0.087, 0.959], [-0.080, 0.966], [-0.085, 0.973], [-0.087, 0.965], [-0.097, 0.965], [-0.097, 0.975], [-0.092, 0.984], [-0.101, 0.980], [-0.108, 0.980], [-0.104, 0.987], [-0.102, 0.993], [-0.115, 1.001], [-0.099, 0.996], [-0.101, 1.007], [-0.090, 1.010], [-0.087, 1.021], [-0.069, 1.021], [-0.052, 1.022], [-0.052, 1.017], [-0.069, 1.010], [-0.064, 1.005], [-0.048, 1.005], [-0.031, 1.005], [-0.031, 0.996], [-0.040, 0.987], [-0.045, 0.980], [-0.052, 0.975], [-0.040, 0.973], [-0.026, 0.968], [-0.020, 0.954], [-0.006, 0.947], [ 0.003, 0.935], [ 0.006, 0.926], [ 0.005, 0.921], [ 0.022, 0.923], [ 0.033, 0.912], [ 0.029, 0.905], [ 0.017, 0.900], [ 0.012, 0.895], [ 0.027, 0.893], [ 0.019, 0.886], [ 0.001, 0.883], [-0.012, 0.884], [-0.029, 0.883], [-0.038, 0.879], [-0.057, 0.881], [-0.062, 0.876], [-0.078, 0.876], [-0.087, 0.872], [-0.030, 0.907], [-0.007, 0.905], [-0.057, 0.916], [-0.025, 0.933], [-0.077, 0.990], [-0.059, 0.993]]) x = np.degrees(xy[:, 0]) y = np.degrees(xy[:, 1]) triangles = np.asarray([ [67, 66, 1], [65, 2, 66], [ 1, 66, 2], [64, 2, 65], [63, 3, 64], [60, 59, 57], [ 2, 64, 3], [ 3, 63, 4], [ 0, 67, 1], [62, 4, 63], [57, 59, 56], [59, 58, 56], [61, 60, 69], [57, 69, 60], [ 4, 62, 68], [ 6, 5, 9], [61, 68, 62], [69, 68, 61], [ 9, 5, 70], [ 6, 8, 7], [ 4, 70, 5], [ 8, 6, 9], [56, 69, 57], [69, 56, 52], [70, 10, 9], [54, 53, 55], [56, 55, 53], [68, 70, 4], [52, 56, 53], [11, 10, 12], [69, 71, 68], [68, 13, 70], [10, 70, 13], [51, 50, 52], [13, 68, 71], [52, 71, 69], [12, 10, 13], [71, 52, 50], [71, 14, 13], [50, 49, 71], [49, 48, 71], [14, 16, 15], [14, 71, 48], [17, 19, 18], [17, 20, 19], [48, 16, 14], [48, 47, 16], [47, 46, 16], [16, 46, 45], [23, 22, 24], [21, 24, 22], [17, 16, 45], [20, 17, 45], [21, 25, 24], [27, 26, 28], [20, 72, 21], [25, 21, 72], [45, 72, 20], [25, 28, 26], [44, 73, 45], [72, 45, 73], [28, 25, 29], [29, 25, 31], [43, 73, 44], [73, 43, 40], [72, 73, 39], [72, 31, 25], [42, 40, 43], [31, 30, 29], [39, 73, 40], [42, 41, 40], [72, 33, 31], [32, 31, 33], [39, 38, 72], [33, 72, 38], [33, 38, 34], [37, 35, 38], [34, 38, 35], [35, 37, 36]]) # Rather than create a Triangulation object, can simply pass x, y and triangles # arrays to triplot directly. It would be better to use a Triangulation object # if the same triangulation was to be used more than once to save duplicated # calculations. plt.figure() plt.gca().set_aspect('equal') plt.triplot(x, y, triangles, 'go-', lw=1.0) plt.title('triplot of user-specified triangulation') plt.xlabel('Longitude (degrees)') plt.ylabel('Latitude (degrees)') plt.show() Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)