Matplotlib.axes.Axes.triplot() in Python

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 = 24
n_radii = 9
min_radius = 0.5
radii = 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: