Matplotlib is a library in Python and it is numerical ā 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.has_data() Function
The Axes.has_data() function in axes module of matplotlib library is used to check if any artists have been added to axes.
Syntax: Axes.has_data(self)
Parameters: This method does not accepts any parameter.
Returns: This method return True if any artists have been added to axes.
Below examples illustrate the matplotlib.axes.Axes.has_data() function in matplotlib.axes:
Example 1:
# ImpleIn Reviewtation of matplotlib functionĀ Ā import matplotlib.pyplot as plt Ā Ā Ā Ā fig, ax1 = plt.subplots( ) ax1.set_xscale( "log" ) ax1.set_yscale( "log" ) ax1.set_adjustable( "datalim" ) Ā Ā ax1.plot([ 1 , 3 , 34 , 4 , 46 , 3 , 7 , 45 , 10 ], Ā Ā Ā Ā Ā Ā Ā Ā Ā [ 1 , 9 , 27 , 8 , 29 , 84 , 78 , 19 , 48 ], Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā "o-" , color = "green" ) Ā Ā ax1.set_xlim( 1e - 1 , 1e2 ) ax1.set_ylim( 1 , 1e2 ) Ā Ā w = ax1.has_data() Ā Ā print ( "Value Return by has_data() :" , w) Ā Ā Ā fig.suptitle('matplotlib.axes.Axes.has_data()\ Ā function Example\n\n', fontweight = "bold" ) Ā Ā fig.canvas.draw() Ā Ā plt.show() |
Output:
Value Return by has_data() : True
Example 2:
# ImpleIn Reviewtation of matplotlib functionĀ Ā import matplotlib.pyplot as plt import matplotlib.tri as tri import numpy as np Ā Ā Ā Ā Ā n_angles = 36 n_radii = 10 min_radius = 2 radii = np.linspace(min_radius, 0.95 , n_radii) Ā Ā Ā Ā Ā angles = np.linspace( 0 , 2 * np.pi, n_angles, Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā endpoint = False ) angles = np.repeat(angles[..., np.newaxis],Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā n_radii, axis = 1 ) angles[:, 1 :: 2 ] + = 2 * np.pi / n_angles Ā Ā Ā Ā Ā x = (radii * np.cos(angles)).flatten() y = (radii * np.sin(angles)).flatten() Ā Ā Ā Ā Ā triang = tri.Triangulation(x, y) Ā Ā Ā Ā Ā triang.set_mask(np.hypot(x[triang.triangles].mean(axis = 1 ), Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā y[triang.triangles].mean(axis = 1 )) Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā Ā < min_radius) fig, ax = plt.subplots() Ā Ā Ā Ā Ā ax.triplot(triang, 'bo-' , lw = 1 , color = "green" ) Ā Ā w = ax.has_data() Ā Ā print ( "Value Return by has_data() :" , w) Ā Ā Ā fig.suptitle('matplotlib.axes.Axes.has_data() function\ Ā Example\n\n', fontweight = "bold" ) Ā Ā fig.canvas.draw() Ā Ā plt.show() |
Output:
Value Return by has_data() : True