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.autoscale() Function
The Axes.autoscale() function in axes module of matplotlib library is used to autoscale the axis view to the data (toggle).
Syntax: Axes.autoscale(self, enable=True, axis=’both’, tight=None)
Parameters: This method accepts the following parameters.
- enable : If this parameter is True (default) turns autoscaling on, False turns it off.
- axis: This parameter is used to which axis to be operate on. {‘both’, ‘x’, ‘y’}
- tight: This parameter is forwarded to autoscale_view.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axes.Axes.autoscale() function in matplotlib.axes:
Example 1:
# Implementation of matplotlib function import numpy as np from matplotlib.path import Path from matplotlib.patches import PathPatch import matplotlib.pyplot as plt vertices = [] codes = [] codes = [Path.MOVETO] + [Path.LINETO]*3 + [Path.CLOSEPOLY] vertices = [(1, 1), (1, 2), (2, 2), (2, 1), (0, 0)] codes += [Path.MOVETO] + [Path.LINETO]*2 + [Path.CLOSEPOLY] vertices += [(4, 4), (5, 5), (5, 4), (0, 0)] vertices = np.array(vertices, float) path = Path(vertices, codes) pathpatch = PathPatch(path, facecolor ='None', edgecolor ='green') fig, ax = plt.subplots() ax.add_patch(pathpatch) ax.autoscale() fig.suptitle('matplotlib.axes.Axes.autoscale() \ function Example\n', fontweight ="bold") fig.canvas.draw() plt.show() |
Output:
Example 2:
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np from matplotlib.collections import EllipseCollection x = np.arange(10) y = np.arange(15) X, Y = np.meshgrid(x, y) XY = np.column_stack((X.ravel(), Y.ravel())) fig, ax = plt.subplots() ec = EllipseCollection(10, 10, 5, units ='y', offsets = XY * 0.5, transOffset = ax.transData, cmap ="inferno") ec.set_array((X * Y).ravel()) ax.add_collection(ec) ax.autoscale_view() ax.set_xlabel('X') ax.set_ylabel('y') cbar = plt.colorbar(ec) cbar.set_label('X + Y') fig.suptitle('matplotlib.axes.Axes.autoscale() function \ Example\n', fontweight ="bold") fig.canvas.draw() plt.show() |
Output:
