Open In App

Matplotlib.artist.Artist.set_sketch_params() in Python

Last Updated : 12 Jul, 2025
Comments
Improve
Suggest changes
Like Article
Like
Report
Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Artist class contains Abstract base class for objects that render into a FigureCanvas. All visible elements in a figure are subclasses of Artist.

matplotlib.artist.Artist.set_sketch_params() method

The set_sketch_params() method in artist module of matplotlib library is used to sets the sketch parameters.
Syntax: Artist.set_sketch_params(self, scale=None, length=None, randomness=None) Parameters: This method accepts the following parameters.
  • scale: This parameter is the amplitude of the wiggle perpendicular to the source line, in pixels.
  • length: This parameter is the length of the wiggle along the line, in pixels.
  • randomness : This parameter is the scale factor by which the length is shrunken or expanded.
Returns: This method does not return any value.
Below examples illustrate the matplotlib.artist.Artist.set_sketch_params() function in matplotlib: Example 1: Python3 1==
# Implementation of matplotlib function
from matplotlib.artist import Artist  
import matplotlib.pyplot as plt 
import matplotlib.colors as mcolors 
import matplotlib.gridspec as gridspec 
import numpy as np 
    
    
plt.rcParams['savefig.facecolor'] = "0.8"
plt.rcParams['figure.figsize'] = 6, 5
    
fig, ax = plt.subplots() 
    
ax.plot([1, 2]) 
    
ax.locator_params("x", nbins = 3) 
ax.locator_params("y", nbins = 5) 
    
ax.set_xlabel('x-label') 
ax.set_ylabel('y-label') 
  
Artist.set_sketch_params(ax, 100, 100, 20) 

fig.suptitle('matplotlib.artist.Artist.set_sketch_params()\
function Example', fontweight ="bold") 

plt.show()
Output: Example 2: Python3 1==
# Implementation of matplotlib function
from matplotlib.artist import Artist  
import matplotlib.pyplot as plt 
import numpy as np 
   
values = np.array([ 
    0.015, 0.166, 0.133,  
    0.159, 0.041, 0.024, 
    0.195, 0.039, 0.161, 
    0.018, 0.143, 0.056, 
    0.125, 0.096, 0.094, 
    0.051, 0.043, 0.021, 
    0.138, 0.075, 0.109, 
    0.195, 0.050, 0.074,  
    0.079, 0.155, 0.020, 
    0.010, 0.061, 0.008]) 
   
values[[3, 14]] += .8
   
fig, (ax, ax2) = plt.subplots(2, 1, sharex = True) 
   
ax.plot(values, "o-", color ="green") 
ax2.plot(values, "o-", color ="green") 
   
ax.set_ylim(.78, 1.)  
ax2.set_ylim(0, .22) 
   
ax.spines['bottom'].set_visible(False) 
ax2.spines['top'].set_visible(False) 
ax.xaxis.tick_top() 
ax.tick_params(labeltop = False) 
ax2.xaxis.tick_bottom() 
   
d = .005
kwargs = dict(transform = ax.transAxes,  
              color ='k', clip_on = False) 
  
ax.plot((-d, +d), (-d, +d), **kwargs)        
ax.plot((1 - d, 1 + d), (-d, +d), **kwargs)  
   
kwargs.update(transform = ax2.transAxes)   
  
ax2.plot((-d, +d), (1 - d, 1 + d), **kwargs) 
ax2.plot((1 - d, 1 + d), (1 - d, 1 + d), **kwargs)  

Artist.set_sketch_params(ax, 1.0, 100.0, 22.0) 
Artist.set_sketch_params(ax2, 1.0, 10.0, 22.0)

fig.suptitle('matplotlib.artist.Artist.set_sketch_params()\
function Example', fontweight ="bold") 

plt.show()
Output:

Practice Tags :

Similar Reads