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.
matplotlib.axes.Axes.set_rasterized() Function
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:
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()
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Output:
Example 2:
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()
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Output:
Last Updated :
30 Apr, 2020
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