# Matplotlib.axis.Tick.set_transform() function in Python

Matplotlib is a library in Python and it is numerical â€“ 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.Tick.set_transform() Function

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

Syntax: Tick.set_transform(self, t)

Parameters: This method accepts the following parameters.

• t: This parameter is the Transform.

Return value: This method does not return any value.

Below examples illustrate the matplotlib.axis.Tick.set_transform() function in matplotlib.axis:
Example 1:

## Python3

 `# Implementation of matplotlib function ``from` `matplotlib.axis ``import` `Tick ``import` `numpy as np   ``import` `matplotlib.pyplot as plt   ``import` `matplotlib.transforms as mtransforms   ``  ` `delta ``=` `0.5``    ` `x ``=` `y ``=` `np.arange(``-``2.0``, ``4.0``, delta)   ``X, Y ``=` `np.meshgrid(x``*``*``2``, 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   ``Tick.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(``-``3``, ``6``)   ``ax.set_ylim(``-``5``, ``5``) `` ` `fig.suptitle('matplotlib.axis.Tick.set_transform() \ ``function Example', fontweight ``=``"bold"``)   ``    ` `plt.show()  `

Output:

Example 2:

## Python3

 `# Implementation of matplotlib function ``from` `matplotlib.axis ``import` `Tick ``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``)   ``Tick.set_transform(col, trans)    ``      ` `ax1.add_collection(col, autolim ``=` `True``)   ``col.set_color(colors)  `` ` `fig.suptitle('matplotlib.axis.Tick.set_transform() \ ``function Example', fontweight ``=``"bold"``)   ``    ` `plt.show()  `

Output:

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