Matplotlib.pyplot.tripcolor() in Python

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
# sample code import matplotlib.pyplot as plt      plt.plot([1, 2, 3, 4], [16, 4, 1, 8])  plt.show()   | 
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
argsandkwargsare 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:
# Implementation of matplotlib function import matplotlib.pyplot as plt import matplotlib.tri as tri import numpy as np       ang = 40rad = 10radm = 0.35radii = 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()  | 
Output:
Example-2:
# 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, 66,  2], [64,  2, 65],                          [63,  3, 64],[ 6,  5,  9],                         [61, 68, 62], [69, 68, 61],                          [ 9,  5, 70], [ 6,  8,  7],                         [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, 70,  5], [ 8,  6,  9],                         [56, 69, 57], [69, 56, 52],                         [70, 10,  9], [54, 53, 55],                          [56, 55, 53], [68, 70,  4],                         [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 = -2y0 = 20zfaces = 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()  | 
Output:
				
					



