Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.
matplotlib.axes.Axes.triplot() Function
The Axes.triplot() function in axes module of matplotlib library is also used to create a unstructured triangular grid as lines and/or markers.
Syntax:
Axes.triplot(ax, *args, **kwargs)Parameters: This method accept the following parameters that are described below:
- x, y: These parameter are the x and y coordinates of the data which is to be plot.
- triangulation: This parameter is a matplotlib.tri.Triangulation object.
- **kwargs: This parameter is Text properties that is used to control the appearance of the labels.
All remaining args and kwargs are the same as for matplotlib.pyplot.plot().
Returns: This returns the list of 2 Line2D containing following:
- The lines plotted for triangles edges.
- The markers plotted for triangles nodes
Below examples illustrate the matplotlib.axes.Axes.triplot() function in matplotlib.axes:
Example-1:
# Implementation of matplotlib function 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, 5, 4], [2, 6, 5], [4, 5, 7], [5, 6, 8], [5, 8, 7], [7, 8, 9], [1, 2, 5], [2, 3, 6]] triang = mtri.Triangulation(x, y, triangles) z = np.cos(1.5 * x) * np.cos(1.5 * y) fig, axs = plt.subplots() axs.tricontourf(triang, z) axs.triplot(triang, 'go-', color ='white') fig.tight_layout() axs.set_title('matplotlib.axes.Axes.triplot() Example') plt.show() |
Output:
Example-2:
# Implementation of matplotlib function 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, 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) fig1, ax1 = plt.subplots() ax1.set_aspect('equal') ax1.triplot(triang, 'go-', lw = 2) ax1.set_title('matplotlib.axes.Axes.triplot() Example') plt.show() |
Output:
