Matplotlib.axes.Axes.set_rasterized() in Python

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. The Axes.set_rasterized() function in axes module of matplotlib library is used to force rasterized (bitmap) drawing in vector backend output.

Syntax: Axes.set_rasterized(self, rasterized) Parameters: This method accepts only one parameters.

• rasterized: This parameter is the boolean value.

Returns: This method does not return any value.

Below examples illustrate the matplotlib.axes.Axes.set_rasterized() 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_rasterized(True)

fig.suptitle('matplotlib.axes.Axes.set_rasterized() \
function Example', fontweight ="bold")

plt.show()

Output: Example 2: Python3

# Implementation of matplotlib function
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.gridspec as gridspec
import numpy as np
 
 
arr = np.arange(100).reshape((10, 10))
norm = mcolors.Normalize(vmin = 0., vmax = 100.)
 
pc_kwargs = {'cmap': 'plasma', 'norm': norm}
 
fig, ax = plt.subplots( )
 
im = ax.pcolormesh(arr, **pc_kwargs)
fig.colorbar(im, ax = ax, shrink = 0.6)
 
ax.set_rasterized(False)

fig.suptitle('matplotlib.axes.Axes.set_rasterized()\
 function Example', fontweight ="bold")

plt.show()

Output: