Matplotlib is a library in Python and it is numerical – 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.Axis.get_transform() Function
The Axis.get_transform() function in axis module of matplotlib library is used to get the Transform instance used by this artist.
Syntax: Axis.get_transform(self)
Parameters: This method does not accepts any parameter.
Return value: This method return the Transform instance used by this artist.
Below examples illustrate the matplotlib.axis.Axis.get_transform() function in matplotlib.axis:
Example 1:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import numpy as np import matplotlib.pyplot as plt import matplotlib.transforms as mtransforms fig, ax = plt.subplots() l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-") l2, = ax.plot([0.1, 0.5, 0.9], [0.5, 0.2, 0.7], "ro-") for l in [l1, l2]: xx = l.get_xdata() yy = l.get_ydata() shadow, = ax.plot(xx, yy) shadow.update_from(l) ot = mtransforms.offset_copy(l.get_transform(), ax.figure, x = 4.0, y =-6.0, units ='points') shadow.set_transform(ot) fig.suptitle("""matplotlib.axis.Axis.get_transform() function Example\n""", fontweight ="bold") plt.show() |
Output:
Example 2:
Python3
# Implementation of matplotlib function from matplotlib.axis import Axis import matplotlib.pyplot as plt from matplotlib import collections, colors, transforms import numpy as np nverts = 50npts = 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) Axis.set_transform(col, trans) ax1.add_collection(col, autolim = True) col.set_color(colors) print("Value Return by get_transform() :\n", col.get_transform()) fig.suptitle("""matplotlib.axis.Axis.get_transform() function Example\n""", fontweight ="bold") plt.show() |
Output:
