Matplotlib.axis.Tick.set_rasterized() function in Python

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_rasterized() Function

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

Syntax: Tick.set_rasterized(self, rasterized) 

Parameters: This method accepts the following parameters. 

• rasterized: This parameter is the boolean value.

Return value: This method does not return any value. 

Below examples illustrate the matplotlib.axis.Tick.set_rasterized() function in matplotlib.axis:
Example 1:

Python3

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


d = np.arange(16).reshape(4,4)
xx, yy = np.meshgrid(np.arange(5), np.arange(5))

fig, ax = plt.subplots()

ax.set_aspect(1)
m = ax.pcolormesh(xx, yy, d)
Tick.set_rasterized(m, True)

fig.suptitle('matplotlib.axis.Tick.set_rasterized() \
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 matplotlib.colors as mcolors
import matplotlib.gridspec as gridspec
import numpy as np


arr = np.arange(20).reshape((4, 5))
norm = mcolors.Normalize(vmin = 0., vmax = 20.)

pc_kwargs = {'cmap': 'BuGn', 'norm': norm}

fig, ax = plt.subplots( )

im = ax.pcolormesh(arr, **pc_kwargs)
fig.colorbar(im, ax = ax, shrink = 0.7)
Tick.set_rasterized(im, False)

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

plt.show()

Output: