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:
# 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:
# 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 = 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 )
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: