# Matplotlib.artist.Artist.get_agg_filter() in Python

• Last Updated : 15 May, 2020

Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Artist class contains Abstract base class for objects that render into a FigureCanvas. All visible elements in a figure are subclasses of Artist.

## Matplotlib.artist.Artist.get_agg_filter() Method

The get_agg_filter() method in artist module of matplotlib library is used to get the filter function to be used for agg filter.

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Syntax: Artist.get_agg_filter(self)

Parameters: This method does not accepts any parameter.

Returns: This method return filter function to be used for agg filter.

Below examples illustrate the matplotlib.artist.Artist.get_agg_filter() function in matplotlib:

Example 1:

 `# Implementation of matplotlib function``import` `numpy as np``import` `matplotlib.pyplot as plt``from` `matplotlib.artist ``import` `Artist `` ` ` ` `xx ``=` `np.random.rand(``16``, ``30``)`` ` `fig, axs ``=` `plt.subplots()`` ` `m ``=` `axs.pcolor(xx)``m.set_zorder(``-``20``)`` ` `# use of get_agg_filter() method``val ``=` `Artist.get_agg_filter(axs)``axs.set_title(``"Value Return by get_agg_filter(): "``              ``+` `str``(val))`` ` `fig.suptitle('matplotlib.artist.Artist.get_agg_filter() \``function Example', fontweight``=``"bold"``)`` ` `plt.show()`

Output:

Example 2:

 `# Implementation of matplotlib function``import` `numpy as np``import` `matplotlib.pyplot as plt``from` `matplotlib.artist ``import` `Artist `` ` ` ` `np.random.seed(``10``*``*``7``)``geeks ``=` `np.random.randn(``40``)`` ` `fig, axs ``=` `plt.subplots()``axs.acorr(geeks, usevlines``=``True``, normed``=``True``,``          ``maxlags``=``30``, lw``=``2``)`` ` `axs.grid(``True``)`` ` `# use of get_agg_filter() method``val ``=` `Artist.get_agg_filter(axs)``axs.set_title(``"Value Return by get_agg_filter(): "` `              ``+` `str``(val))`` ` `fig.suptitle('matplotlib.artist.Artist.get_agg_filter() \``function Example', fontweight``=``"bold"``)`` ` `plt.show()`

Output:

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