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:
# 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:
# 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: