Matplotlib.axes.Axes.get_aspect() in Python
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_aspect() Function
The Axes.get_aspect() function in axes module of matplotlib library is used to get the aspect of the axis scaling, i.e. the ratio of y-unit to x-unit
Syntax:Axes.get_aspect(self)
Parameters: This method does not accepts any parameters.
Return value: This method returns the aspect value.
Below examples illustrate the matplotlib.axes.Axes.get_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 ) 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 ) w = ax1.get_aspect() w1 = ax2.get_aspect() ax1.set_title( "Axes 1\n Ratio : " + str (w)) ax2.set_title( "Axes 2\n Ratio : " + str (w1)) fig.suptitle('matplotlib.axes.Axes.get_aspect() \ function Example\n\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 = 36 n_radii = 10 min_radius = 2 radii = np.linspace(min_radius, 0.95 , n_radii) angles = np.linspace( 0 , 2 * np.pi, n_angles, endpoint = False ) angles = np.repeat(angles[..., np.newaxis], n_radii, axis = 1 ) angles[:, 1 :: 2 ] + = 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" ) ax1.set_aspect( 'equal' ) ax1.triplot(triang, 'bo-' , lw = 1 , color = "green" ) w = ax.get_aspect() w1 = ax1.get_aspect() ax.set_title( "Axes 1\n Ratio : " + str (w)) ax1.set_title( "Axes 2\n Ratio : " + str (w1)) fig.suptitle('matplotlib.axes.Axes.get_aspect() \ function Example\n\n', fontweight = "bold" ) fig.canvas.draw() plt.show() |
Output: