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.set_rasterized() Function
The Axis.set_rasterized() function in axis module of matplotlib library is used to force rasterized (bitmap) drawing in vector backend output.
Syntax: Axis.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.Axis.set_rasterized() function in matplotlib.axis:
Example 1:
# Implementation of matplotlib function from matplotlib.axis import Axis
import numpy as np
import matplotlib.pyplot as plt
d = np.arange( 49 ).reshape( 7 , 7 )
xx, yy = np.meshgrid(np.arange( 8 ), np.arange( 8 ))
fig, ax = plt.subplots()
ax.set_aspect( 1 )
m = ax.pcolormesh(xx, yy, d)
Axis.set_rasterized(m, True )
fig.suptitle('matplotlib.axis.Axis.set_rasterized() \ function Example\n', fontweight = "bold" )
plt.show() |
Output:
Example 2:
# Implementation of matplotlib function from matplotlib.axis import Axis
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 )
Axis.set_rasterized(im, False )
fig.suptitle('matplotlib.axis.Axis.set_rasterized() \ function Example\n', fontweight = "bold" )
plt.show() |
Output: