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Matplotlib.axis.Tick.set_sketch_params() function in Python

  • Last Updated : 10 Jun, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. It is an amazing visualization library in Python for 2D plots of arrays and used for working with the broader SciPy stack.

Matplotlib.axis.Tick.set_sketch_params() Function

The Tick.set_sketch_params() function in axis module of matplotlib library is used to sets the sketch parameters. 
 

Syntax: Tick.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.

Return value: This method does not return any value. 

Below examples illustrate the matplotlib.axis.Tick.set_sketch_params() function in matplotlib.axis:
Example 1:



Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
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, 3, 4, 5] , [2, 3,6,2,5])  
         
ax.locator_params("x", nbins = 3)  
ax.locator_params("y", nbins = 5)  
         
ax.set_xlabel('x-label')  
ax.set_ylabel('y-label')  
       
Tick.set_sketch_params(ax, 50, 50, 10)
  
fig.suptitle('matplotlib.axis.Tick.set_sketch_params() \
function Example', fontweight ="bold")  
     
plt.show() 

Output:

Example 2:

Python3




# Implementation of matplotlib function
from matplotlib.axis import Tick
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,  
    0.918, 0.143, 0.056,  
    0.125, 0.096, 0.094,  
    0.051, 0.043, 0.021,  
    0.138, 0.075, 0.109,  
    0.195, 0.750, 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 = .001
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)   
     
Tick.set_sketch_params(ax, 1.0, 10.0, 25.0)  
Tick.set_sketch_params(ax2, 2.0, 100.0, 50.0
  
fig.suptitle('matplotlib.axis.Tick.set_sketch_params() \
function Example', fontweight ="bold")  
     
plt.show() 

Output: 

 

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