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: