Matplotlib.axis.Axis.get_transformed_clip_path_and_affine() function in Python
Last Updated :
08 Jun, 2020
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_transformed_clip_path_and_affine() Function
The Axis.get_transformed_clip_path_and_affine() function in axis module of matplotlib library is used to get the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation.
Syntax: Axis.get_transformed_clip_path_and_affine(self)
Parameters: This method does not accepts any parameter.
Return value: This method return the clip path with the non-affine part of its transformation applied, and the remaining affine part of its transformation.
Below examples illustrate the matplotlib.axis.Axis.get_transformed_clip_path_and_affine() function in matplotlib.axis:
Example 1:
Image used:
Python3
from matplotlib.axis import Axis
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.cbook as cbook
with cbook.get_sample_data( 'image.PNG' ) as image_file:
image = plt.imread(image_file)
fig, ax = plt.subplots()
im = ax.imshow(image)
patch = patches.Rectangle(( 50 , 50 ), 200 , 200 ,
transform = ax.transData)
val = Axis.get_transformed_clip_path_and_affine(im)
ax.set_title( "Value Return by get_transformed_clip_path_and_affine(): "
+ str (val))
fig.suptitle(
, fontweight = "bold")
plt.show()
|
Output:
Example 2:
Python3
from matplotlib.axis import Axis
import numpy as np
import matplotlib.cm as cm
import matplotlib.pyplot as plt
from matplotlib.path import Path
from matplotlib.patches import PathPatch
delta = 0.025
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) * 2
path = Path([[ 0 , 1 ], [ 1 , 0 ], [ 0 , - 1 ], [ - 1 , 0 ], [ 0 , 1 ]])
patch = PathPatch(path, facecolor = 'none' )
fig, ax = plt.subplots()
ax.add_patch(patch)
im = ax.imshow(Z,
interpolation = 'bilinear' ,
cmap = cm.gray,
origin = 'lower' ,
extent = [ - 3 , 3 , - 3 , 3 ],
clip_path = patch,
clip_on = True )
val = Axis.get_transformed_clip_path_and_affine(im)
print ( "Value Return by get_transformed_clip_path_and_affine(): " )
for i in val:
print (i)
fig.suptitle(
, fontweight = "bold")
plt.show()
|
Output:
Value Return by get_transformed_clip_path_and_affine():
Path(array([[ 0., 1.],
[ 1., 0.],
[ 0., -1.],
[-1., 0.],
[ 0., 1.]]), None)
Affine2D(
[[ 82.66666667 0. 328. ]
[ 0. 61.6 237.6 ]
[ 0. 0. 1. ]])
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