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_adjustable() Function
The Axes.get_adjustable() function in axes module of matplotlib library is used to get which parameter the Axes is given to achieve a given aspect.
Syntax: Axes.get_adjustable(self)
Parameters: This method does not accepts any parameters.
Return value: This method returns the adjustable value.
Below examples illustrate the matplotlib.axes.Axes.get_adjustable() 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_xlim(1e1, 1e3) ax1.set_ylim(1e2, 1e3) ax1.set_aspect(1) ax1.set_title("Axes 1") ax2.set_xscale("log") ax2.set_yscale("log") ax2.set_adjustable("datalim") ax2.plot([1, 113, 10], [1, 119, 100], "o-") ax2.set_xlim(1e-1, 1e2) ax2.set_ylim(1e-1, 1e3) ax2.set_aspect(1) ax2.set_title("Axes 2") w = ax1.get_adjustable() w1 = ax2.get_adjustable() ax1.text(20, 400, " Value return by\n get_adjustable() : " +str(w)) ax2.text(1, 200, " Value return by \nget_adjustable() : \n " +str(w1)) fig.suptitle('matplotlib.axes.Axes.get_adjustable() 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 = 40n_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_aspect('equal') ax.set_title("Axes 1") ax1.set_aspect('equal') ax1.set_adjustable("datalim") ax1.triplot(triang, 'bo-', lw = 1, color = "green") ax1.set_title("Axes 2") w = ax.get_adjustable() w1 = ax1.get_adjustable() ax.text(-1.15, -3.5, " Value return by\n get_adjustable() : " +str(w)) ax1.text(-1, 2.5, " Value return by \nget_adjustable() : \n " +str(w1)) fig.suptitle('matplotlib.axes.Axes.get_adjustable() function \ Example\n', fontweight ="bold") fig.canvas.draw() plt.show() |
Output:
