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Matplotlib.artist.Artist.get_sketch_params() in Python

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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.get_sketch_params() method

The get_sketch_params() method in artist module of matplotlib library is used to get the sketch parameters for the artist.

Syntax: Artist.get_sketch_params(self)

Parameters: This method does not accepts any parameter.

Returns: This method return the sketch parameters for the artist.

Below examples illustrate the matplotlib.artist.Artist.get_sketch_params() function in matplotlib:

Example 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'
     
ax.text(0.2, 1.8, "Sketch Parameters : "
        +str(Artist.get_sketch_params(ax)),  
        fontweight ="bold")  
  
fig.suptitle('matplotlib.artist.Artist.get_sketch_params()\
function Example', fontweight ="bold"
  
plt.show()


Output:

Example 2:




# 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)
     
ax.text(5, .95, "Sketch Parameters : "
        + str(Artist.get_sketch_params(ax)),  
        fontweight ="bold")  
  
fig.suptitle('matplotlib.artist.Artist.get_sketch_params()\
function Example', fontweight ="bold"
  
plt.show()


Output:



Last Updated : 10 May, 2020
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