Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. Pyplot is a state-based interface to a Matplotlib module which provides a MATLAB-like interface.
Matplotlib.pyplot.tricontourf()
The tricontourf() function in pyplot module of matplotlib library is used to draw contours on an unstructured triangular grid.
Syntax: matplotlib.pyplot.tricontourf(\*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.
- Z: This parameter is the array of values to contour, one per point in the triangulation.
- **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
Note: tricontourf-only keyword arguments is antialiased which is a bool enable antialiasing which used in contours on an unstructured triangular grid.
Below examples illustrate the matplotlib.pyplot.tricontourf() function in matplotlib.pyplot:
Example 1:
Python3
#Implementation of matplotlib functionimport matplotlib.pyplot as plt import matplotlib.tri as mtri import numpy as np # Create triangulation. x = np.asarray([0, 1, 0, 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(2.5 * x*x) + np.sin(2.5 * x*x) t = plt.tricontourf(triang, z)plt.title('matplotlib.pyplot.tricontourf() Example\n', fontsize=14, fontweight='bold')plt.show() |
Output:
Example 2:
Python3
#Implementation of matplotlib functionimport matplotlib.pyplot as plt import matplotlib.tri as tri import numpy as np n_angles = 60n_radii = 10min_radius = 0.35radii = np.linspace(min_radius, 0.95, 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 = (10 * radii * np.cos(angles)).flatten() y = (10 * radii * np.sin(angles)).flatten() z = (np.cos(4*(radii)**2) * np.sin((angles)**2)).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) tcf = plt.tricontourf(triang, z)plt.colorbar(tcf) plt.title('matplotlib.pyplot.tricontourf() Example\n', fontsize=14, fontweight='bold')plt.show() |
Output:
