Matplotlib is a library in Python and it is numerical – mathematical extension for NumPy library. The Artist class contains Abstract base class for objects that render into a FigureCanvas. All visible elements in a figure are subclasses of Artist.
matplotlib.artist.Artist.set_snap() method
The set_snap() method in artist module of matplotlib library is used to set the snapping behavior.
Syntax: Artist.set_snap(self, snap)
Parameters: This method accepts the following parameters.
- snap: This parameter contains the boolean value or None.
Returns: This method does not return any value.
Below examples illustrate the matplotlib.artist.Artist.set_snap() function in matplotlib:
Example 1:
# Implementation of matplotlib function from matplotlib.artist import Artist import matplotlib.pyplot as plt from mpl_toolkits.axisartist.axislines import Subplot fig = plt.figure() ax = Subplot(fig, 111 ) fig.add_subplot(ax) ax.axis[ "left" ].set_visible( False ) ax.axis[ "top" ].set_visible( False ) Artist.set_snap(ax, True ) fig.suptitle('matplotlib.artist.Artist.set_snap()\ function Example', fontweight = "bold" ) plt.show() |
Output:
Example 2:
# Implementation of matplotlib function from matplotlib.artist import Artist import numpy as np import matplotlib.cm as cm import matplotlib.pyplot as plt import matplotlib.cbook as cbook 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) Artist.set_snap(ax, None ) fig.suptitle('matplotlib.artist.Artist.set_snap()\ function Example', fontweight = "bold" ) plt.show() |
Output: