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 importmatplotlib.pyplot as plt importmatplotlib.tri as mtri importnumpy 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 importmatplotlib.pyplot as plt importmatplotlib.tri as tri importnumpy 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:
 
				 
					



