Matplotlib.axes.Axes.get_transformed_clip_path_and_affine() in Python
Last Updated :
30 Apr, 2020
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_transformed_clip_path_and_affine() Function
The Axes.get_transformed_clip_path_and_affine() function in axes 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: Axes.get_transformed_clip_path_and_affine(self)
Parameters: This method does not accepts any parameter.
Returns: 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.axes.Axes.get_transformed_clip_path_and_affine() function in matplotlib.axes:
Example 1:
Image used:
import matplotlib.pyplot as plt
import matplotlib.patches as patches
import matplotlib.cbook as cbook
with cbook.get_sample_data( 'loggf.PNG' ) as image_file:
image = plt.imread(image_file)
fig, ax = plt.subplots()
im = ax.imshow(image)
patch = patches.Rectangle(( 0 , 0 ), 260 , 200 ,
transform = ax.transData)
ax.set_title( "Value Return by get_transformed_clip_path_and_affine(): "
+ str (im.get_transformed_clip_path_and_affine()))
fig.suptitle('matplotlib.axes.Axes.get_transformed_clip_path_and_affine()\
function Example\n\n', fontweight = "bold" )
plt.show()
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Output:
Example 2:
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 )
print ( "Value Return by get_transformed_clip_path_and_affine(): " )
for i in im.get_transformed_clip_path_and_affine():
print (i)
fig.suptitle('matplotlib.axes.Axes.get_transformed_clip_path_and_affine()\
function Example\n\n', fontweight = "bold" )
plt.show()
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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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