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Matplotlib.pyplot.setp() function 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. There are various plots which can be used in Pyplot are Line Plot, Contour, Histogram, Scatter, 3D Plot, etc.

Matplotlib.pyplot.setp() function

The setp() function in pyplot module of matplotlib library is used to set the property on an artist object. 
 



Syntax: matplotlib.pyplot.setp(obj, \*args, \*\*kwargs)
 

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



  • obj: This parameter is the artist object.
  • **kwargs: There are different keyword arguments which are accepted.

Returns: This method does not returns any value. 

Below examples illustrate the matplotlib.pyplot.setp() function in matplotlib.pyplot: 
 

Example 1: 




#Implementation of matplotlib function
import numpy as np
import matplotlib.pyplot as plt
   
   
def tellme(s):
    plt.title(s, fontsize=16)
    plt.draw()
plt.clf()
plt.setp(plt.gca(), autoscale_on=False)
   
tellme('matplotlib.pyplot.setp() function Example')
plt.show()

Output: 

Example 2: 




# Implementation of matplotlib function
import matplotlib
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
    
delta = 0.25
x = np.arange(-3.0, 5.0, delta)
y = np.arange(-1.3, 2.5, delta)
X, Y = np.meshgrid(x, y)
Z = (np.exp(-X**2 - Y**2) - np.exp(-(X - 1)**2 - (Y - 1)**2))
    
im = plt.imshow(Z, interpolation='bilinear'
                origin='lower',
                cmap="bone",
                extent=(-3, 3, -2, 2))
  
levels = np.arange(-1.2, 1.6, 0.2)
CS = plt.contour(Z, levels,
                 origin='lower'
                 cmap='Greens',
                 linewidths=2,
                 extent=(-3, 3, -2, 2))
  
zc = CS.collections[6]
plt.setp(zc, linewidth=2)  
plt.clabel(CS, levels,
           inline=1,
           fmt='%1.1f',
           fontsize=14)
   
plt.title('matplotlib.pyplot.setp() Example')
  
plt.show()

Output: 

 


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