.. _pylab_examples-triplot_demo:

pylab_examples example code: triplot_demo.py
============================================



.. plot:: /home/tcaswell/source/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`)