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.
#Sample Code
# Implementation of matplotlib function import matplotlib.pyplot as plt import numpy as np # make an agg figure fig, ax = plt.subplots() ax.plot([1, 2, 3]) ax.set_title('matplotlib.axes.Axes function') fig.canvas.draw() plt.show() |
Output:
matplotlib.axes.Axes.set_aspect() Function
The Axes.set_aspect() function in axes module of matplotlib library is used to set the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit.
Syntax:
Axes.set_aspect(self, aspect, adjustable=None, anchor=None, share=False)
Parameters: This method accepts the following parameters.
- aspect : This parameter accepts the following value {‘auto’, ‘equal’} or num.
- adjustable : This defines which parameter will be adjusted to meet the required aspect.
- anchor : This parameter is used to define where the Axes will be drawn if there is extra space due to aspect constraints.
- share: This parameter is used to apply the settings to all shared Axes.
Return value: This method does not return any value.
Below examples illustrate the matplotlib.axes.Axes.set_aspect() function in matplotlib.axes:
Example-1:
# ImpleIn Reviewtation of matplotlib function import matplotlib.pyplot as plt fig, (ax1, ax2) = plt.subplots(1, 2) ax1.set_xscale("log") ax1.set_yscale("log") ax1.set_adjustable("datalim") ax1.plot([1, 3, 34, 4, 46, 3, 7, 45, 10], [1, 9, 27, 8, 29, 84, 78, 19, 48], "o-", color ="green") ax1.set_xlim(1e-1, 1e2) ax1.set_ylim(1, 1e2) ax1.set_title("No set_aspect") ax2.set_xscale("log") ax2.set_yscale("log") ax2.set_adjustable("datalim") ax2.plot([1, 3, 34, 4, 46, 3, 7, 45, 10], [1, 9, 27, 8, 29, 84, 78, 19, 48], "o-", color ="green") ax2.set_xlim(1e-1, 1e2) ax2.set_ylim(1, 1e2) ax2.set_aspect(2) ax2.set_title("set_aspect value = 2") fig.suptitle('matplotlib.axes.Axes.set_aspect() \ function Example\n', fontweight ="bold") fig.canvas.draw() plt.show() |
Output:
Example-2:
# ImpleIn Reviewtation of matplotlib function import matplotlib.pyplot as plt import matplotlib.tri as tri import numpy as np n_angles = 20n_radii = 10min_radius = 2radii = np.linspace(min_radius, 0.95, n_radii) angles = np.linspace(0, 4 * np.pi, n_angles, endpoint = False) angles = np.repeat(angles[..., np.newaxis], n_radii, axis = 1) angles[:, 1::2] += np.pi / n_angles x = (radii * np.cos(angles)).flatten() y = (radii * np.sin(angles)).flatten() triang = tri.Triangulation(x, y) triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1), y[triang.triangles].mean(axis = 1)) < min_radius) fig, (ax, ax1) = plt.subplots(1, 2) ax.triplot(triang, 'bo-', lw = 1, color = "green") ax.set_title("No set_aspect") ax1.set_aspect('equal') ax1.triplot(triang, 'bo-', lw = 1, color = "green") ax1.set_title("set_aspect value ='equal'") fig.suptitle('matplotlib.axes.Axes.set_aspect() \ function Example\n', fontweight ="bold") fig.canvas.draw() plt.show() |
Output:
