Matplotlib.axes.Axes.get_rasterization_zorder() in Python

Last Updated : 30 Apr, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Axes Class contains most of the figure elements: Axis, Tick, Line2D, Text, Polygon, etc., and sets the coordinate system. And the instances of Axes supports callbacks through a callbacks attribute.

matplotlib.axes.Axes.get_rasterization_zorder() Function

The Axes.get_rasterization_zorder() function in axes module of matplotlib library is used to return the zorder value below which artists will be rasterized.

Syntax: Axes.get_rasterization_zorder(self) Parameters: This method does not accepts any parameters. Returns: This method return the zorder value below which artists will be rasterized.

Below examples illustrate the matplotlib.axes.Axes.get_rasterization_zorder() function in matplotlib.axes: Example 1:

Python3

# Implementation of matplotlib function 
import numpy as np 
import matplotlib.pyplot as plt 
  

d = np.arange(100).reshape(10, 10) 
xx, yy = np.meshgrid(np.arange(11), np.arange(11)) 
  
fig, ax = plt.subplots() 
  
ax.set_aspect(1) 
m = ax.pcolormesh(xx, yy, d) 
m.set_zorder(-15) 
ax.set_rasterization_zorder(-5) 

w = ax.get_rasterization_zorder()
ax.text( 2, 9.5, "Rasterization Zorder Value : " + str(w))
 
fig.suptitle('matplotlib.axes.Axes.get_rasterization_zorder() \
function Example', fontweight ="bold") 

plt.show()

Output:

Example 2:

Python3

# Implementation of matplotlib function 
import numpy as np 
import matplotlib.pyplot as plt 


xx = np.random.rand(16, 30) 
  
fig, (ax3, ax4) = plt.subplots(1, 2) 
  
m = ax3.pcolor(xx) 
m.set_zorder(-20) 

w = ax3.get_rasterization_zorder()
ax3.set_title("Rasterization Zorder Value : " + str(w)) 
  
m = ax4.pcolor(xx) 
m.set_zorder(-20) 

ax4.set_rasterization_zorder(-10) 
w = ax4.get_rasterization_zorder()
ax4.set_title("Rasterization Zorder Value : " + str(w))
 
fig.suptitle('matplotlib.axes.Axes.get_rasterization_zorder()\
 function Example', fontweight ="bold") 

plt.show()