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Matplotlib.pyplot.tripcolor() in Python
  • 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.

Sample Code

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

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Output:

matplotlib.pyplot.tripcolor() Function

The tripcolor() function in pyplot module of matplotlib library is used to create a pseudocolor plot of an unstructured triangular grid.

Syntax: matplotlib.pyplot.tripcolor(*args, alpha=1.0, norm=None, cmap=None, vmin=None, vmax=None, shading=’flat’, facecolors=None, **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. 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.tripcolor() function in matplotlib.pyplot:

Example-1:

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# Implementation of matplotlib function
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
   
   
ang = 40
rad = 10
radm = 0.35
radii = np.linspace(radm, 0.95, rad)
   
angles = np.linspace(0, 1.5 * np.pi, ang)
angles = np.repeat(angles[..., np.newaxis], rad,
                   axis = 1)
  
angles[:, 1::2] += np.pi / ang
   
x = (radii * np.cos(angles)).flatten()
y = (radii * np.sin(angles)).flatten()
z = (np.sin(4 * radii) * np.cos(4 * angles)).flatten()
   
triang = tri.Triangulation(x, y)
triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1),
                         y[triang.triangles].mean(axis = 1))
                < radm)
   
fig1, ax1 = plt.subplots()
ax1.set_aspect('equal')
tpc = ax1.tripcolor(triang, z, shading ='flat')
fig1.colorbar(tpc)
  
fig1.suptitle('matplotlib.pyplot.tripcolor() function\
 Example\n\n', fontweight ="bold")
plt.show()

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Output:

Example-2:

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# Implementation of matplotlib function
import matplotlib.pyplot as plt
import matplotlib.tri as tri
import numpy as np
   
xy = np.asarray([
    [-0.057, 0.881], [-0.062, 0.876], 
    [-0.078, 0.876], [-0.087, 0.872],
    [-0.030, 0.907], [-0.007, 0.905],
    [-0.057, 0.916], [-0.025, 0.933],
    [-0.045, 0.897], [-0.057, 0.895], 
    [-0.073, 0.900], [-0.087, 0.898],
    [-0.090, 0.904], [-0.069, 0.907],
    [-0.069, 0.921], [-0.080, 0.919],
    [-0.073, 0.928], [-0.052, 0.930],
    [-0.048, 0.942], [-0.062, 0.949],
    [-0.054, 0.958], [-0.069, 0.954],
    [-0.087, 0.952], [-0.087, 0.959],
    [-0.080, 0.966], [-0.085, 0.973],
    [-0.087, 0.965], [-0.097, 0.965],
    [-0.097, 0.975], [-0.092, 0.984],
    [-0.101, 0.980], [-0.108, 0.980],
    [-0.104, 0.987], [-0.102, 0.993], 
    [-0.115, 1.001], [-0.099, 0.996],
    [-0.101, 1.007], [-0.090, 1.010], 
    [-0.087, 1.021], [-0.069, 1.021],
    [-0.052, 1.022], [-0.052, 1.017], 
    [-0.069, 1.010], [-0.064, 1.005],
    [-0.048, 1.005], [-0.031, 1.005],
    [-0.031, 0.996], [-0.040, 0.987],
    [-0.045, 0.980], [-0.052, 0.975],
    [-0.040, 0.973], [-0.026, 0.968],
    [-0.020, 0.954], [-0.006, 0.947],
    [ 0.003, 0.935], [ 0.006, 0.926],
    [ 0.005, 0.921], [ 0.022, 0.923],
    [ 0.033, 0.912], [ 0.029, 0.905],
    [ 0.017, 0.900], [ 0.012, 0.895],
    [ 0.027, 0.893], [ 0.019, 0.886],
    [ 0.001, 0.883], [-0.012, 0.884],
    [-0.029, 0.883], [-0.038, 0.879],
    [-0.073, 0.928], [-0.052, 0.930], 
    [-0.048, 0.942], [-0.062, 0.949],
    [-0.054, 0.958], [-0.069, 0.954],
    [-0.087, 0.952], [-0.087, 0.959],
    [-0.080, 0.966], [-0.085, 0.973],
    [-0.087, 0.965], [-0.097, 0.965],
    [-0.077, 0.990], [-0.059, 0.993]])
x, y = np.rad2deg(xy).T
   
triangles = np.asarray([[ 1, 662], [642, 65], 
                        [633, 64],[ 659],
                        [61, 68, 62], [69, 68, 61], 
                        [ 95, 70], [ 687],
                        [21, 24, 22], [17, 16, 45], 
                        [20, 17, 45], [21, 25, 24],
                        [27, 26, 28], [20, 72, 21],
                        [25, 21, 72], [45, 72, 20],
                        [25, 28, 26], [44, 73, 45],
                        [72, 45, 73], [28, 25, 29], 
                        [29, 25, 31], [43, 73, 44], 
                        [73, 43, 40], [72, 73, 39], 
                        [72, 31, 25], [42, 40, 43], 
                        [31, 30, 29], [39, 73, 40],
                        [ 4, 705], [ 869],
                        [56, 69, 57], [69, 56, 52],
                        [70, 109], [54, 53, 55], 
                        [56, 55, 53], [68, 704],
                        [52, 56, 53], [11, 10, 12],
                        [69, 71, 68], [68, 13, 70], 
                        [10, 70, 13], [51, 50, 52], 
                        [13, 68, 71], [52, 71, 69], 
                        [12, 10, 13], [71, 52, 50], 
                        [71, 14, 13], [50, 49, 71],
                        [49, 48, 71], [14, 16, 15], 
                        [14, 71, 48], [17, 19, 18],
                        [17, 20, 19], [48, 16, 14],
                        [48, 47, 16], [47, 46, 16], 
                        [16, 46, 45], [23, 22, 24],
                        [42, 41, 40], [72, 33, 31],
                        [32, 31, 33], [39, 38, 72], 
                        [33, 72, 38], [33, 38, 34], 
                        [37, 35, 38], [34, 38, 35],
                        [35, 37, 36]])
   
xmid = x[triangles].mean(axis = 1)
ymid = y[triangles].mean(axis = 1)
x0 = -2
y0 = 20
zfaces = np.exp(-0.3 * ((xmid - x0) + (ymid - y0) ))
   
fig3, ax3 = plt.subplots()
ax3.set_aspect('equal')
tpc = ax3.tripcolor(x, y, triangles, facecolors = zfaces,
                    edgecolors ='k')
fig3.colorbar(tpc)
ax3.set_title('matplotlib.pyplot.tripcolor() Example')
plt.show()

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Output:

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