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.Axis.get_path_effects() Function
The Axis.get_path_effects() function in axis module of matplotlib library is used to get the property of set_path_effects.
Syntax: Axis.get_path_effects(self)
Parameters: This method does not accepts any parameter.
Return value: This method return the property of set_path_effects
Below examples illustrate the matplotlib.axis.Axis.get_path_effects() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import numpy as np import matplotlib.patheffects as path_effects fig, ax = plt.subplots() t = ax.text( 0.02 , 0.5 , 'GeeksForGeeks' , fontsize = 40 , weight = 1000 , va = 'center' ) t.set_path_effects([path_effects.PathPatchEffect(offset = ( 4 , - 4 ), hatch = 'xxxx' , facecolor = 'gray' ), path_effects.PathPatchEffect(edgecolor = 'white' , linewidth = 1.1 , facecolor = 'black' )]) print ( "Value Return by get_path_effects() : \n" ) for i in Axis.get_path_effects(t): print (i) fig.suptitle( """matplotlib.axis.Axis.get_path_effects() function Example\n""" , fontweight = "bold") plt.show() |
Output:
Value Return by get_path_effects() : <matplotlib.patheffects.PathPatchEffect object at 0x0A6EDBD0> <matplotlib.patheffects.PathPatchEffect object at 0x0A6EDDB0>
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt import matplotlib.patheffects as PathEffects import numpy as np fig, ax1 = plt.subplots() ax1.imshow([[ 1 , 2 ], [ 2 , 3 ]]) txt = ax1.annotate( "Fourth" , ( 1. , 1. ), ( 0. , 0 ), arrowprops = dict (arrowstyle = "->" , connectionstyle = "angle3" , lw = 2 ), size = 20 , ha = "center" , path_effects = [PathEffects.withStroke(linewidth = 3 , foreground = "w" )]) txt.arrow_patch.set_path_effects([ PathEffects.Stroke(linewidth = 5 , foreground = "w" ), PathEffects.Normal()]) ax1.grid( True , linestyle = "-" ) pe = [PathEffects.withStroke(linewidth = 3 , foreground = "w" )] for l in ax1.get_xgridlines() + ax1.get_ygridlines(): l.set_path_effects(pe) print ( "Value Return by get_path_effects() : \n" ) for l in ax1.get_xgridlines() + ax1.get_ygridlines(): for i in Axis.get_path_effects(l): print (i) fig.suptitle( """matplotlib.axis.Axis.get_path_effects() function Example\n""" , fontweight = "bold") plt.show() |
Output:
Value Return by get_path_effects() : <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50> <matplotlib.patheffects.withStroke object at 0x0A98EF50>