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Matplotlib.figure.Figure.colorbar() in Python

  • Last Updated : 30 Apr, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The figure module provides the top-level Artist, the Figure, which contains all the plot elements. This module is used to control the default spacing of the subplots and top level container for all plot elements.

matplotlib.figure.Figure.colorbar() function

The colorbar() method of figure module of matplotlib library is used to add a colorbar to a plot.

Syntax: colorbar(self, mappable, cax=None, ax=None, use_gridspec=True, **kw)

Parameters: This accept the following parameters that are described below:

  • mappable: This parameter is mandatory for the Figure.colorbar method.
  • cax : This parameter is the Axes into which the colorbar will be drawn.
  • ax : This parameter is the parent axes from which space for a new colorbar axes will be stolen.
  • use_gridspec : This parameter is used to create an instance of Subplot using the gridspec module.

Returns: This method does not return any value.



Below examples illustrate the matplotlib.figure.Figure.colorbar() function in matplotlib.figure:

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.figure.Figure.colorbar() \
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
     
n_angles = 26
n_radii = 10
min_radius = 0.35
radii = np.linspace(min_radius,
                    0.95,
                    n_radii)
   
angles = np.linspace(0, 2 * 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) * np.cos(3 * 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')
tcf = ax1.tricontourf(triang, z)
fig1.colorbar(tcf)
ax1.tricontour(triang, z, colors ='g')
  
fig1.suptitle('matplotlib.figure.Figure.colorbar()\
function Example\n\n', fontweight ="bold")
  
plt.show()

Output:

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