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.get_transform() Function
The Axes.get_transform() function in axes module of matplotlib library is used to get the Transform instance used by this artist
Syntax: Axes.get_transform(self)
Parameters: This method does not accepts any parameter.
Returns: This method return the Transform instance used by this artist
Below examples illustrate the matplotlib.axes.Axes.get_transform() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function 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.axes.Axes.get_transform() \ function Example', fontweight = "bold" ) plt.show() |
Output:
Example 2:
# Implementation of matplotlib function 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 ) col.set_transform(trans) ax1.add_collection(col, autolim = True ) col.set_color(colors) print ( "Value Return by get_transform() :\n" , col.get_transform()) fig.suptitle('matplotlib.axes.Axes.get_transform() \ function Example', fontweight = "bold" ) plt.show() |
Output:
Value Return by get_transform() : Affine2D( [[1.38888889 0. 0. ] [0. 1.38888889 0. ] [0. 0. 1. ]])