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Matplotlib.pyplot.tricontour() in Python

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  • Last Updated : 11 Apr, 2020

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. There are various plots which can be used in Pyplot are Line Plot, Contour, Histogram, Scatter, 3D Plot, etc.

Sample Code




# sample code
import matplotlib.pyplot as plt 
    
plt.plot([1, 2, 3, 4], [16, 4, 1, 8]) 
plt.show() 

Output:

matplotlib.pyplot.tricontour() Function

The tricontour() function in pyplot module of matplotlib library is used to draw contours on an unstructured triangular grid.

Syntax:

matplotlib.pyplot.tricontour(*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 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. pcolor().

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.pyplot.tricontour() function in matplotlib.pyplot:

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(3 * x) * np.cos(6 * y)+np.sin(6 * x)
      
fig, axs = plt.subplots()
t = axs.tricontourf(triang, z)
axs.tricontour(triang, z, colors ='white')
fig.colorbar(t)
  
fig.suptitle('matplotlib.pyplot.tricontour() 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 = 26
n_radii = 10
min_radius = 0.35
radii = np.linspace(min_radius, 
                    0.95, n_radii)
   
angles = np.linspace(0, 3 * 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(16 * radii) * np.cos(3 * angles)+np.sin(8 * radii)).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')
tcf = ax1.tricontourf(triang, z)
fig1.colorbar(tcf)
ax1.tricontour(triang, z, colors ='k')
fig1.suptitle('matplotlib.pyplot.tricontour() Example'
  
plt.show()

Output:


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