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

The set_transform() method in artist module of matplotlib library is used to set the artist transform.

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Syntax: Artist.set_transform(self, t)

Parameters: This method accepts only one parameters.

• t : This parameter is the Transform.

Returns: This method does not return any value.

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

Example 1:

 `# Implementation of matplotlib function``from` `matplotlib.artist ``import` `Artist ``import` `numpy as np ``import` `matplotlib.pyplot as plt ``import` `matplotlib.transforms as mtransforms `` ` `   ` `delta ``=` `0.25`` ` `x ``=` `y ``=` `np.arange(``-``3.0``, ``3.0``, delta) ``X, Y ``=` `np.meshgrid(x, y) `` ` `Z1 ``=` `np.exp(``-``X``*``*``2` `-` `Y``*``*``2``) ``Z2 ``=` `np.exp(``-``(X ``-` `1``)``*``*``2` `-` `(Y ``-` `1``)``*``*``2``) ``Z ``=` `(Z1 ``-` `Z2) ``   ` `transform ``=` `mtransforms.Affine2D().rotate_deg(``30``) ``fig, ax ``=` `plt.subplots() ``       ` `im ``=` `ax.imshow(Z, interpolation ``=``'none'``, ``               ``origin ``=``'lower'``, ``               ``extent ``=``[``-``2``, ``4``, ``-``3``, ``2``],  ``               ``clip_on ``=` `True``) ``   ` `trans_data ``=` `transform ``+` `ax.transData ``Artist.set_transform(im, trans_data) ``   ` `x1, x2, y1, y2 ``=` `im.get_extent() ``ax.plot([x1, x2, x2, x1, x1],  ``        ``[y1, y1, y2, y2, y1], ``        ``"ro-"``, ``        ``transform ``=` `trans_data) ``   ` `ax.set_xlim(``-``5``, ``5``) ``ax.set_ylim(``-``4``, ``4``) `` ` `plt.title(``"""matplotlib.artist.Artist.set_transform()``function Example"""``, fontweight``=``"bold")`` ` `plt.show()`

Output:

Example 2:

 `# Implementation of matplotlib function``from` `matplotlib.artist ``import` `Artist ``import` `matplotlib.pyplot as plt ``from` `matplotlib ``import` `collections, colors, transforms ``import` `numpy as np `` ` `    ` `nverts ``=` `50``npts ``=` `100``    ` `r ``=` `np.arange(nverts) ``theta ``=` `np.linspace(``0``, ``2` `*` `np.pi, nverts) `` ` `xx ``=` `r ``*` `np.sin(theta) ``yy ``=` `r ``*` `np.cos(theta) `` ` `spiral ``=` `np.column_stack([xx, yy]) ``    ` `rs ``=` `np.random.RandomState(``19680801``) ``    ` `xyo ``=` `rs.randn(npts, ``2``) ``    ` `colors ``=` `[colors.to_rgba(c) ``          ``for` `c ``in` `plt.rcParams[``'axes.prop_cycle'``].by_key()[``'color'``]] ``    ` `fig, ax1 ``=` `plt.subplots() ``    ` `col ``=` `collections.RegularPolyCollection( ``    ``7``, sizes ``=` `np.``abs``(xx) ``*` `10.0``,  ``    ``offsets ``=` `xyo,  ``    ``transOffset ``=` `ax1.transData) ``   ` `trans ``=` `transforms.Affine2D().scale(fig.dpi ``/` `72.0``) ``Artist.set_transform(col, trans)  ``   ` `ax1.add_collection(col, autolim ``=` `True``) ``col.set_color(colors)`` ` `plt.title(``"""matplotlib.artist.Artist.set_transform()``function Example"""``, fontweight``=``"bold")`` ` `plt.show()`

Output:

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