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: