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.set_clip_path() Function
The Axes.set_clip_path() function in axes module of matplotlib library is used to set the artist’s clip path.
Syntax: Axes.set_clip_path(self, path, transform=None)
Parameters: This method accepts only two parameters.
- path: This parameter is the clip path.
- transform: This parameter in which Path is converted to a TransformedPath using transform.
Returns: This method does not return any value.
Below examples illustrate the matplotlib.axes.Axes.set_clip_path() function in matplotlib.axes:
Example 1:
Input Image:
# Implementation of matplotlib function 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) im.set_clip_path(patch) fig.suptitle('matplotlib.axes.Axes.set_clip_path() \ function Example\n\n', fontweight = "bold" ) plt.show() |
Output:
Example 2:
# Implementation of matplotlib function 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 ) im.set_clip_path(patch) fig.suptitle('matplotlib.axes.Axes.set_clip_path() \ function Example\n\n', fontweight = "bold" ) plt.show() |
Output: