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# 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:

 `# 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:

 `# 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:

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