Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.
Unstructured Triangular Grid
An unstructured grid can be defined as the part of the Euclidean plane or diagram that can be fit together in a pattern with no spaces in between two shapes. Unstructured grid can be triangle or tetrahedra in an irregular pattern. Unstructured Triangular Grid can be drawn from an irregularly shaped polygon using the Ruppert’s algorithm.
Here the task is to draw a unstructured triangular grid as lines and/or markers in Python using Matplotlib. In order to do this task, you can use the triplot() function and we require some modules from matplotlib and numpy library.
Example 1: Creating and plotting unstructured triangular grids.
Python3
# Importing modules import matplotlib.pyplot as plt import matplotlib.tri as tri import numpy as np n_angles = 24n_radii = 9min_radius = 0.5radii = np.linspace(min_radius, 0.9, n_radii) angles = np.linspace(0, 6 * 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() triang = tri.Triangulation(x, y) triang.set_mask(np.hypot(x[triang.triangles].mean(axis=1), y[triang.triangles].mean(axis=1)) < min_radius) plt.triplot(triang, 'o-', lw=1) plt.title('Example 1') plt.show() |
Output:
Example 2: Using the TriFinder object to highlight the unstructured triangular grid.
Python3
# Importing modules import matplotlib.pyplot as plt from matplotlib.tri import Triangulation from matplotlib.patches import Polygon import numpy as np def Trigolo1(tri): if tri == -1: points = [0, 0, 0] else: points = triang.triangles[tri] xs = triang.x[points] ys = triang.y[points] polygon.set_xy(np.column_stack([xs, ys])) def Trigolo2(event): if event.inaxes is None: tri = -1 else: tri = trifinder(event.xdata, event.ydata) Trigolo1(tri) plt.title('Example 2\nTriangle No : %i' % tri) event.canvas.draw() # Create a Triangulation. ang = 16rad = 5mrad = 0.25radii = np.linspace(mrad, 0.95, rad) angletri = np.linspace(0, 2 * np.pi, ang, endpoint=False) angletri = np.repeat(angletri[..., np.newaxis], rad, axis=1) angletri[:, 1::2] += np.pi / ang x = (radii*np.cos(angletri)).flatten() y = (radii*np.sin(angletri)).flatten() triang = Triangulation(x, y) triang.set_mask(np.hypot(x[triang.triangles].mean(axis=1), y[triang.triangles].mean(axis=1)) < mrad) # Use the triangulation's default TriFinder object. trifinder = triang.get_trifinder() # Setup plot and callbacks. plt.subplot(111, aspect='equal') plt.triplot(triang, 'o-') polygon = Polygon([[0, 0], [0, 0]], facecolor='y') Trigolo1(-1) plt.gca().add_patch(polygon) plt.gcf().canvas.mpl_connect('motion_notify_event', Trigolo2) plt.show() |
Output:
Example 3: Example showing the plot the triangulation.
Python3
import matplotlib.pyplot as plt import matplotlib.tri as mtri import numpy as np # Create triangulation. x = np.asarray([0, 1, 2, 3, 0.5, 1.5, 2.5, 1, 2, 1.5]) y = np.asarray([0, 0, 0, 0, 1.0, 1.0, 1.0, 2, 2, 3.0]) triangles = [[0, 1, 4], [1, 2, 5], [2, 3, 6], [1, 5, 4], [2, 6, 5], [4, 5, 7], [5, 6, 8], [5, 8, 7], [7, 8, 9]] triang = mtri.Triangulation(x, y, triangles) z = np.cos(1.5 * x) * np.cos(1.5 * y) plt.tricontourf(triang, z) plt.triplot(triang, 'go-') plt.title('Example 3') plt.show() |
Output:
